Growth of Dehalococcoides spp. and increased abundance of reductive dehalogenase genes in anaerobic PCB-contaminated sediment microcosms

Polychlorinated biphenyls (PCBs) contaminate 19% of US Superfund sites and represent a serious risk to human and environmental health. One promising strategy to remediate PCB-contaminated sediments utilizes organohalide-respiring bacteria (OHRB) that dechlorinate PCBs.

However, functional genes that act as biomarkers for PCB dechlorination processes (i.e., reductive dehalogenase genes) are poorly understood. Here, we developed anaerobic sediment microcosms that harbor an OHRB community dominated by the genus Dehalococcoides. During the 430-day microcosm incubation, Dehalococcoides 16S rRNA sequences increased two orders of magnitude to 10⁷ copies/g of sediment, and at the same time, PCB118 decreased by as much as 70%. In addition, the OHRB community dechlorinated a range of penta- and tetra-chlorinated PCB congeners including PCBs 66, 70?+?74?+?76, 95, 90?+?101, and PCB110 without exogenous electron donor. We quantified candidate reductive dehalogenase (RDase) genes over a 430-day incubation period and found rd14, a reductive dehalogenase that belongs to Dehalococcoides mccartyi strain CG5, was enriched to 10⁷ copies/g of sediment. At the same time, pcbA5 was enriched to only 10⁵ copies/g of sediment. A survey for additional RDase genes revealed sequences similar to strain CG5’s rd4 and rd8. In addition to demonstrating the PCB dechlorination potential of native microbial communities in contaminated freshwater sediments, our results suggest candidate functional genes with previously unexplored potential could serve as biomarkers of PCB dechlorination processes.

     

Protective effects of thymoquinone against acrylamide-induced liver,kidney and brain oxidative damage in rats

Environmental Science and Pollution Research - Acrylamide (AA), an industrial monomer, may cause multi-organ toxicity through induction of oxidative stress and inflammation. The antioxidant...     

Biosynthesized silver nanoparticles regulate the iron status in the spleen of Plasmodium chabaudi–infected mice

Environmental Science and Pollution Research - Malaria is a dangerous disease affecting millions around the globe. Biosynthesized nanoparticles are used against a variety of diseases including...     

Dengue fever awareness: effect of an educational intervention on nursing students,Tanta, Egypt

Environmental Science and Pollution Research - Dengue fever (DF) is one of the world’s most important vector-borne illnesses. In 2017, Egypt experienced a dengue outbreak. This study aimed to...     

Fine-resolution mapping of wildfire fuel types for Canada: Fuzzy logic modeling for an Alberta pilot area

The Canadian Forest Fire Danger Rating System (CFFDRS) is used daily across Canada for evaluating forest fire danger. Fuel-type information is one of the inputs required by the models used in the CFFDRS. In this project, three fuel-type maps with a 25 m resolution were produced for a pilot study area located in Alberta using land cover only; land cover and biomass; and, land cover, biomass and leaf area index data derived from satellite imagery. The relationships between inputs and fuel types were determined mainly by the opinions of forest fire scientists and incorporated into a computer program using fuzzy set methodology. Not all the CFFDRS fuel types could be distinguished using these inputs; three of the coniferous types had to be grouped into one common fuel type. Overall accuracy was between 74 and 83% based on ground-truth comparisons. The most accurate map resulted from land cover and biomass data. Detailed accuracy assessment indicated that the overall accuracy increased up to 86% if ambiguous fuel type identification was considered. No combination of inputs was able to define a fuel type with absolute certainty, which is a reflection of differing expert opinions and the small number of inputs used to produce the maps.     

An Experimental Methodology for Monitoring Contaminant Transport Through Geotechnical Centrifuge Models

In this paper, an attempt has been made to highlight an experimental methodology for monitoring contaminant transport through locally available silty soil and commercially available clay in geotechnical centrifuge models, for different compaction states. Use of multiple depth sensors to determine depth distribution of sodium chloride in the soil column has been detailed. The obtained results have been compared with argentometric method. To validate the centrifuge modelling, modelling of models has been used. The test setup developed can simulate contaminant transport mechanisms through the soil mass, which is approximately 10 m deep, over a period of 600 days. R _e and P _e are found to be N times higher in the centrifuge models. These numbers are found to be several orders less than unity. This indicates that laminar flow prevails and the dominating Cl⁻ transport mechanism in centrifuge is diffusion. The study also highlights the fact that the geotechnical centrifuge modelling can be used as a viable alternative to field scale experimentation.     

Assessing Respiratory Morbidity Through Pollution Status and Meteorological Conditions for Delhi

The study focuses on assessing the status of respiratory morbidity in Delhi over a four years period from 2000–2003. An attempt was made to investigate the role of important pollutants (SO₂, NO₂, SPM and RSPM) and various meteorological factors (temperature minimum & maximum, relative humidity at 0830 and 1730 hrs. and wind speed) in being responsible for respiratory admissions on account of COPD, asthma and emphysema. The study showed that winter months had greater exposure risk as pollutants often get trapped in the lower layers of atmosphere resulting in high concentrations. Statistical analysis revealed that two pollutants have significant positive correlation with the number of COPD cases viz., SPM (r = 0.474; p < 0.01) and RSPM (r = 0.353; p < 0.05), while a meteorological factor temperature (minimum) has a significant negative correlation (r = −0.318; p < 0.05) with COPD. Stepwise multiple regression analysis was performed for COPD as dependent variable and R² value of 0.33 was obtained indicating that SPM and RH(1730) were able to explain 33 percent variability in COPD. The partial correlation of SPM and RH(1730) on COPD was higher than any other combination and therefore they can be regarded as important contributing variables on COPD.     

The Influence of Linear Elements on Plant Species Diversity of Mediterranean Rural Landscapes: Assessment of Different Indices and Statistical Approaches

This paper mainly aims to study the linear element influence on the estimation of vascular plant species diversity in five Mediterranean landscapes modeled as land cover patch mosaics. These landscapes have several core habitats and a different set of linear elements -habitat edges or ecotones, roads or railways, rivers, streams and hedgerows on farm land- whose plant composition were examined. Secondly, it aims to check plant diversity estimation in Mediterranean landscapes using parametric and non-parametric procedures, with two indices: Species richness and Shannon index.Land cover types and landscape linear elements were identified from aerial photographs. Their spatial information was processed using GIS techniques. Field plots were selected using a stratified sampling design according to relieve and tree density of each habitat type. A 50×20 m² multi-scale sampling plot was designed for the core habitats and across the main landscape linear elements. Richness and diversity of plant species were estimated by comparing the observed field data to ICE (Incidence-based Coverage Estimator) and ACE (Abundance-based Coverage Estimator) non-parametric estimators.The species density, percentage of unique species, and alpha diversity per plot were significantly higher (p < 0.05) in linear elements than in core habitats. ICE estimate of number of species was 32% higher than of ACE estimate, which did not differ significantly from the observed values. Accumulated species richness in core habitats together with linear elements, were significantly higher than those recorded only in the core habitats in all the landscapes. Conversely, Shannon diversity index did not show significant differences.     

Preparation of 2-mercaptobenzothiazole-derivatized mesoporous silica and removal of Hg(ii) from aqueous solution

Mesoporous silicas (SBA-15 and MCM-41) have been functionalized by two different methods. Using the heterogeneous route the silylating agent, 3-chloropropyltriethoxysilane, was initially immobilized onto the mesoporous silica surface to give the chlorinated mesoporous silica Cl-SBA-15 or Cl-MCM-41. In a second reaction a multifunctionalized N,S donor compound (2-mercaptobenzothiazol) was incorporated to obtain the functionalized silicas denoted as MBT-SBA-15-Het and MBT-MCM-41-Het. Using the homogeneous route, the functionalization was achieved via the one step reaction of the mesoporous silica with an organic ligand containing the chelating functions, to give the modified mesoporous silicas denoted as MBT-SBA-15-Hom or MBT-MCM-41-Hom. The functionalized mesoporous silicas were employed as adsorbents for the regeneration of aqueous solutions at pH 6 contaminated with Hg(ii) at room temperature. Results obtained indicate that mercury adsorption was higher in the mesoporus silicas prepared by the homogeneous method, and the maximum adsorption value (0.24 +/- 0.02 mmol Hg(ii) g(-1)) was obtained for MBT-SBA-15-Hom. The chemically stability in acid medium of the functionalized silicas, possibility its regeneration washing with concentrate HCl, resulting in the reuse of the adsorbent material for several cycles.     

Status of the Riparian Ecosystem in the Upper San Pedro River, Arizona: Application of an Assessment Model

A portion of Arizona’s San Pedro River is managed as a National Riparian Conservation Area but is potentially affected by ground-water withdrawals beyond the conservation area borders. We applied an assessment model to the Conservation Area as a basis for monitoring long-term changes in riparian ecosystem condition resulting from changes in river water availability, and collected multi-year data on a subset of the most sensitive bioindicators. The assessment model is based on nine vegetation bioindicators that are sensitive to changes in surface water or ground water. Site index scores allow for placement into one of three condition classes, each reflecting particular ranges for site hydrology and vegetation structure. We collected the bioindicator data at 26 sites distributed among 14 reaches that had similar stream flow hydrology (spatial flow intermittency) and geomorphology (channel sinuosity, flood-plain width). Overall, 39% of the riparian corridor fell within condition class 3 (the wettest condition), 55% in condition class 2, and 6% in the driest condition class. Condition class 3 reaches have high cover of herbaceous wetland plants (e.g., Juncus and Schoenoplectus spp.) along the perennial stream channel and dense, multi-aged Populus-Salix woodlands in the flood plain, sustained by shallow ground water in the stream alluvium. In condition class 2, intermittent stream flows result in low cover of streamside wetland herbs, but Populus-Salix remain abundant in the flood plain. Perennial wetland plants are absent from condition class 1, reflecting highly intermittent stream flows; the flood plain is vegetated by Tamarixa small tree that tolerates the deep and fluctuating ground water levels that typify this reach type. Abundance of herbaceous wetland plants and growth rate of Salix gooddingii varied between years with different stream flow rates, indicating utility of these measures for tracking short-term responses to hydrologic change. Repeat measurement of all bioindicators will indicate long-term trends in hydro-vegetational condition.