The Detection Rate of Enteric Viruses and <Emphasis Type="Italic">Clostridium difficile</Emphasis> in a Waste Water Treatment Plant Effluent

Waste water treatment plant (WWTP) is considered as an important source of surface water contamination by enteric pathogens. In this study, we describe the occurrence of enteric viruses (group A rotaviruses, noroviruses, astroviruses, sapoviruses, hepatitis A virus, and hepatitis E virus) and Clostridium difficile in the effluent of a wastewater treatment plant during a 1-year period. Enteric viruses were simultaneously and efficiently concentrated in a single step using methacrylate monolithic chromatographic support. Rotaviruses, noroviruses (genogroup I and II), and sapoviruses were detected in all 12 concentrated samples, whereas astroviruses were not detected in August and September and hepatitis A and E viruses were not detected at all. Clostridium difficile was detected in all samples and altogether 121 strains were isolated and grouped into 32 different ribotypes of which 014/020 and 010 were most prevalent. Pathogens detected in WWTP effluent partially reflect the epidemiological situation of enteric viruses and C. difficile in human population and open the discussion on implementation of possible techniques for virus and bacteria removal from WWTP effluent prior to release into the surface water system.     

Status of the Southern Carpathian forests in the long-term ecological research network

Air pollution, bulk precipitation, throughfall, soil condition, foliar nutrients, as well as forest health and growth were studied in 2006–2009 in a long-term ecological research (LTER) network in the Bucegi Mountains, Romania. Ozone (O₃) was high indicating a potential for phytotoxicity. Ammonia (NH₃) concentrations rose to levels that could contribute to deposition of nutritional nitrogen (N) and could affect biodiversity changes. Higher that 50% contribution of acidic rain (pH?<?5.5) contributed to increased acidity of forest soils. Foliar N concentrations for Norway spruce (Picea abies), Silver fir (Abies alba), Scots pine (Pinus sylvestris), and European beech (Fagus sylvatica) were normal, phosphorus (P) was high, while those of potassium (K), magnesium (Mg), and especially of manganese (Mn) were significantly below the typical European or Carpathian region levels. The observed nutritional imbalance could have negative effects on forest trees. Health of forests was moderately affected, with damaged trees (crown defoliation >25%) higher than 30%. The observed crown damage was accompanied by the annual volume losses for the entire research forest area up to 25.4%. High diversity and evenness specific to the stand type’s structures and local climate conditions were observed within the herbaceous layer, indicating that biodiversity of the vascular plant communities was not compromised.     

Improving the sampling strategy of the Joint Danube Survey 3 (2013) by means of multivariate statistical techniques applied on selected physico-chemical and biological data

The concept of basin-wide Joint Danube Survey (JDS) was launched by the International Commission for the Protection of the Danube River (ICPDR) as a tool for investigative monitoring under the Water Framework Directive (WFD), with a frequency of 6 years. The first JDS was carried out in 2001 and its success in providing key information for characterisation of the Danube River Basin District as required by WFD lead to the organisation of the second JDS in 2007, which was the world’s biggest river research expedition in that year. The present paper presents an approach for improving the survey strategy for the next planned survey JDS3 (2013) by means of several multivariate statistical techniques. In order to design the optimum structure in terms of parameters and sampling sites, principal component analysis (PCA), factor analysis (FA) and cluster analysis were applied on JDS2 data for 13 selected physico-chemical and one biological element measured in 78 sampling sites located on the main course of the Danube. Results from PCA/FA showed that most of the dataset variance (above 75 %) was explained by five varifactors loaded with 8 out of 14 variables: physical (transparency and total suspended solids), relevant nutrients (N–nitrates and P–orthophosphates), feedback effects of primary production (pH, alkalinity and dissolved oxygen) and algal biomass. Taking into account the representation of the factor scores given by FA versus sampling sites and the major groups generated by the clustering procedure, the spatial network of the next survey could be carefully tailored, leading to a decreasing of sampling sites by more than 30 %. The approach of target oriented sampling strategy based on the selected multivariate statistics can provide a strong reduction in dimensionality of the original data and corresponding costs as well, without any loss of information.     

Platinum (IV) recovery from chloride solution by functionalized acrylic copolymers

Two acrylic adsorbents with different morphological structures and bearing amidoethylenamine and thiol groups were obtained and used for platinum sorption from chloride solution by the batch method. Physico-chemical parameters that influence adsorption such as initial Pt(IV) concentration, stirring time, pH, and adsorbent amount were investigated. The thermodynamic parameters of Pt(IV) sorption on the synthesized adsorbent were also evaluated based on Langmuir and Freundlich isotherms. Thermodynamic parameters estimated from Langmuir constants indicated that the adsorption is spontaneous, exothermic and there is a disordered state at the molecular level. The models used to analyze the sorption rate led to the conclusion that the most important step in the sorption of Pt(IV) could be both particle diffusion and chemical reaction of [PtCl₆]⁻ with amine functional groups. Thus, both the ion exchange and complex formation mechanisms can occur via nitrogen atoms in the recovery of Pt(IV) on the studied adsorbent.     

Exploring the association between working memory and driving performance in Parkinson's disease

Objective: The aim of this study was to explore whether varying levels of operational and tactical driving task demand differentially affect drivers with Parkinson's disease (PD) and control drivers in their sign recall.

Methods: Study participants aged between 50 and 70 years included a group of drivers with PD (n = 10) and a group of age- and sex-matched control drivers (n = 10). Their performance in a sign recall task was measured using a driving simulator.

Results: Drivers in the control group performed better than drivers with PD in a sign recall task, but this trend was not statistically significant (P =.43). In addition, regardless of group membership, subjects' performance differed according to varying levels of task demand. Performance in the sign recall task was more likely to drop with increasing task demand (P =.03). This difference was significant when the variation in task demand was associated with a cognitive task; that is, when drivers were required to apply the instructions from working memory.

Conclusions: Although the conclusions drawn from this study are tentative, the evidence presented here is encouraging with regard to the use of a driving simulator to examine isolated cognitive functions underlying driving performance in PD. With an understanding of its limitations, such driving simulation in combination with functional assessment batteries measuring physical, visual, and cognitive abilities could comprise one component of a multitiered system to evaluate medical fitness to drive.     

New international long-term ecological research on air pollution effects on the Carpathian Mountain forests,Central Europe

An international cooperative project on distribution of ozone in the Carpathian Mountains, Central Europe was conducted from 1997 to 1999. Results of that project indicated that in large parts of the Carpathian Mountains, concentrations of ozone were elevated and potentially phytotoxic to forest vegetation. That study led to the establishment of new long-term studies on ecological changes in forests and other ecosystems caused by air pollution in the Retezat Mountains, Southern Carpathians, Romania and in the Tatra Mountains, Western Carpathians on the Polish-Slovak border. Both of these important mountain ranges have the status of national parks and are Man & the Biosphere Reserves. In the Retezat Mountains, the primary research objective was to evaluate how air pollution may affect forest health and biodiversity. The main research objective in the Tatra Mountains was to evaluate responses of natural and managed Norway spruce forests to air pollution and other stresses. Ambient concentrations of ozone (O(3)), sulfur dioxide (SO(2)), nitrogen oxides (NO(x)) as well as forest health and biodiversity changes were monitored on densely distributed research sites. Initial monitoring of pollutants indicated low levels of O(3), SO(2), and NO(x) in the Retezat Mountains, while elevated levels of O(3) and high deposition of atmospheric sulfur (S) and nitrogen (N) have characterized the Tatra Mountains. In the Retezat Mountains, air pollution seems to have little effect on forest health; however, there was concern that over a long time, even low levels of pollution may affect biodiversity of this important ecosystem. In contrast, severe decline of Norway spruce has been observed in the Tatra Mountains. Although bark beetle seems to be the immediate cause of that decline, long-term elevated levels of atmospheric N and S depositions and elevated O(3) could predispose trees to insect attacks and other stresses. European and US scientists studied pollution deposition, soil and plant chemistry, O(3)-sensitive plant species, forest insects, and genetic changes in the Retezat and Tatra Mountains. Results of these investigations are presented in a GIS format to allow for a better understanding of the changes and the recommendations for effective management in these two areas.     

Dynamic extreme values modeling and monitoring by means of sea shores water quality biomarkers and valvometry

Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter ??_t,τ, beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.     

Driving in mild cognitive impairment: The role of depressive symptoms

Objectives: Previous studies indicate a negative association between depression and driving fitness in the general population. Our goal was to cover a gap in the literature and to explore the link between depressive symptoms and driving behavior in individuals with mild cognitive impairment (MCI) through the use of a driving simulator experiment.

Methods: Twenty-four individuals with MCI (mean age = 67.42, SD = 7.13) and 23 cognitively healthy individuals (mean age = 65.13, SD = 7.21) were introduced in the study. A valid driving license and regular car use served as main inclusion criteria. Data collection included a neurological/neuropsychological assessment and a driving simulator evaluation. Depressive symptomatology was assessed with the Patient Health Questionnaire (PHQ-9).

Results: Significant interaction effects indicating a greater negative impact of depressive symptoms in drivers with MCI than in cognitively healthy drivers were observed in the case of various driving indexes, namely, average speed, accident risk, side bar hits, headway distance, headway distance variation, and lateral position variation. The associations between depressive symptoms and driving behavior remained significant after controlling for daytime sleepiness and cognition.

Conclusions: Depressive symptoms could be a factor explaining why certain patients with MCI present altered driving skills. Therefore, interventions for treating the depressive symptoms of individuals with MCI could prove to be beneficial regarding their driving performance.     

Biodegradation Behavior of Composite Films with Poly (Vinyl Alcohol) Matrix

The main objective of this study was to develop biodegradable, composite materials, based on poly (vinyl alcohol), bacterial cellulose and chitosan for possible application in packaging industry. Two composite materials were prepared, one containing poly (vinyl alcohol) (PVA) and bacterial cellulose (BC), named PVA/BC, and the other containing PVA, BC but also chitosan (CTS), named PVA/BC/CTS. The biodegradation behavior was studied in a fed-batch bioreactor, in aerobic and anaerobic conditions, using activated sludge. Biodegradation tests were based on weight loss measurements. Structural changes were confirmed by Fourier transform infrared spectroscopy (FTIR) and the morphological ones by scanning electron microscopy (SEM). After 4?weeks, the biodegradation experiments have shown a relative high degradation of the PVA/BC/CTS film compared with the PVA/BC one. These results were confirmed by spectral analysis and also by SEM images. Besides, the SEM images revealed that biodegradation occurs also inside the composite materials, not only on the surface.     

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

Background

This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.

Results

Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <?40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=?above-average) or low (=?below-average) correlation coefficients.

Conclusions

LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites.