QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes

The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R ²) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

     

Understanding the impact of waste disposal sites on soil quality for agricultural production: A case study of the Kiteezi landfill,Uganda

Leachate from waste disposal sites (WDS) can significantly affect the soil physical, chemical and biological qualities, reducing soil health and agricultural productivity. However, there is a paucity of data on soil quality for understanding soil health impact due to WDS in Uganda. This study's aim was to understand, using the Kiteezi landfill site, how WDS impact soil properties. Soil samples were collected over 4 months in and around the landfill from three locations, and the soil quality data of the nearby area were used as baseline data for assessing the impact on soil due to WDS in the area. There were significant increases in the concentration of all studied parameters at the landfill except total N. The concentrations of ammonium (14.84 ± 1.76 mg/kg), nitrate (127.96 ± 18.36 mg/kg), and pH (7.8) were above the optimum levels. The levels of available P (181.4 ± 28.9 mg/kg) and exchangeable bases; K (2.23 ± 0.24 mg/kg), Na (1.17 ± 0.14 mg/kg), Mg (3.35 ± 0.3 mg/kg) and Ca (14 ± 1.1 mg/kg) cmol (+)/kg were optimal for plant growth. The calculated CEC of 20.75 cmol (+)/kg) showed that soils have a good potential to supply plant nutrients. Heavy metal levels were still below the permissible limit. Hence, the study shows that although WDS may contribute to the increase of soil fertility, they can potentially reduce the overall productivity of soil by increasing nutrient levels beyond optimum levels.     

Vertical characterization of soil contamination using multi-way modeling – A case study

This study describes application of chemometric multi-way modeling approach to analyze the dataset pertaining to soils of industrial area with a view to assess the soil/sub-soil contamination, accumulation pathways and mobility of contaminants in the soil profiles. The three-way (sampling depths, chemical variables, sampling sites) dataset on heavy metals in soil samples collected from three different sites in an industrial area, up to a depth of 60 m each was analyzed using three-way Tucker3 model validated for stability and goodness of fit. A two component Tucker3 model, explaining 66.6% of data variance, allowed interpretation of the data information in all the three modes. The interpretation of core elements revealing interactions among the components of different modes (depth, variables, sites) allowed inferring more realistic information about the contamination pattern of soils both along the horizontal and vertical coordinates, contamination pathways, and mobility of contaminants through soil profiles, as compared to the traditional data analysis techniques. It concluded that soils at site-1 and site-2 are relatively more contaminated with heavy metals of both the natural as well as anthropogenic origins, as compared to the soil of site-3. Moreover, the accumulation pathways of metals for upper shallow layers and deeper layers of soils in the area were differentiated. The information generated would be helpful in developing strategies for remediation of the contaminated soils for reducing the subsequent risk of ground-water contamination in the study region.     

Artificial neural network modeling of the river water quality—A case study

The paper describes the training, validation and application of artificial neural network (ANN) models for computing the dissolved oxygen (DO) and biochemical oxygen demand (BOD) levels in the Gomti river (India). Two ANN models were identified, validated and tested for the computation of DO and BOD concentrations in the Gomti river water. Both the models employed eleven input water quality variables measured in river water over a period of 10 years each month at eight different sites. The performance of the ANN models was assessed through the coefficient of determination (R²) (square of the correlation coefficient), root mean square error (RMSE) and bias computed from the measured and model computed values of the dependent variables. Goodness of the model fit to the data was also evaluated through the relationship between the residuals and model computed values of DO and BOD. The model computed values of DO and BOD by both the ANN models were in close agreement with their respective measured values in the river water. Relative importance and contribution of the input variables to the model output was evaluated through the partitioning approach. The identified ANN models can be used as tools for the computation of water quality parameters.     

In-silico screening of naturally derived phytochemicals against SARS-CoV Main protease

Environmental Science and Pollution Research - Coronavirus disease 2019 (COVID-19) is a rapidly growing pandemic that requires urgent therapeutic intervention. Finding potential anti COVID-19 drugs...     

Sustainable use of stormwater for irrigation case study: Manly Golf Course

Sustainability has become an increasingly used term, but what does it mean in terms of practice. This research will look at the harvesting of captured stormwater for the irrigation of urban playing fields and what the implications are for catchment hydrology, local community, and local council. This research aims to identify, understand and determine the catchment conditions that may hinder the stormwater quality and quantity for capture and reuse, as well as determining whether the stormwater harvesting will be sustainable. Research methods for this project will include systemic analysis in order to further investigate the assumptions being made in the study. Manly Golf Club has relied on groundwater extraction supplemented by potable supplies for irrigation, however potable supplies are no longer available. It has been proposed to provide irrigation supplies from stormwater via onsite storage and groundwater recharge. Monitored stormwater entering the Golf Course from the adjacent Cemetery Creek sub-catchment for pollutants, have indicated that it may be suitable for irrigation with treatment and may reduce problems generated by overuse of groundwater. The proposal will provide environmental benefit through reduced pollution loads being discharged directly to receiving waters and cessation of use of potable supplies by the Club. Social and economic benefits are expected to be gained and will be monitored as part of an ongoing research program.     

Distribution of nitrogen species in groundwater aquifers of an industrial area in alluvial Indo-Gangetic Plains—a case study

The groundwater samples collected from the shallow and deep groundwater aquifers of an industrial area of the Kanpur city (Uttar Pradesh, India) were analyzed for the concentration levels and distribution pattern of nitrogenous species, such as nitrate-nitrogen (NO₃-N), nitrite-nitrogen (NO₂-N), ammonical-nitrogen (NH₄-N), organic-nitrogen (Org-N) and total Kjeldahl-nitrogen (TKN) to identify the possible contamination source. Geo-statistical approach was adopted to determine the distribution and extent of the contaminant plume. In the groundwater aquifers NO₃-N, NO₂-N, NH₄-N, TKN, Org-N and Total-N ranged from 0.10 to 64.10, BDL (below detection limit)-6.57, BDL-39.00, 7.84–202.16, 1.39–198.97 and 8.89–219.43 mg l⁻¹, respectively. About 42% and 26% of the groundwater samples of the shallow and deep groundwater aquifers, respectively, exceeded the BIS (Bureau of Indian Standards) guideline value of 10 mg l⁻¹ for NO₃-N and may pose serious health hazards to the people of the area. The results of the study revealed that the groundwater aquifers of the study area are highly contaminated with the nitrate and indicates point source pollution of nitrate in the study area.     

Uptake and translocation of metals in Spinacia oleracea L. grown on tannery sludge-amended and contaminated soils: effect on lipid peroxidation, morpho-anatomical changes and antioxidants

The plants of Spinacia oleracea L. grown on contaminated soil (CS) and different amendments of tannery sludge (TS) have shown high accumulation of metals in its edible part. The accumulation of toxic metal (Cr) in the leaves of the plants grown on CS was recorded as 40.67 microgg(-1)dw. However, the leaves of the plants grown on 100% TS have accumulated about two times (70.80 microgg(-1)dw) higher Cr than the 10% TS (31.21 microgg(-1)dw). Among growth parameters, the root length was more affected at 90 d than the shoot length, number of leaves and leaf area. The study of scanning electron micrographs showed 29.31% increase in stomatal length in the leaves of the plants grown on CS as compared to garden soil (GS), which served as control, however it decreased in the plants grown on higher amendments of TS. The decrease in MDA content at initial period of exposure and lower amendment was recorded in the leaves, whereas, significant increase (>10% TS onward) was observed with increase in tannery sludge ratio at 90 d as compared to GS. A coordinated increase in all the studied antioxidants (cysteine, non-protein thiol, ascorbic acid, carotenoid contents) was found up to 75 d of growth. At 90 d, most of the antioxidant decreased as compared to 75 d causing oxidative stress as evidenced by increased level of lipid peroxidation and decreased chlorophyll and protein contents. Maximum increase of 181.43% in MDA content and maximum decrease of 53.69% in total chlorophyll content was recorded in the leaves of the plants grown on 100% TS after 90 d of growth. The plants grown on CS have shown an increase in shoot length, number of leaves, leaf area, photosynthetic pigments and protein contents and in all the studied antioxidants. Thus, these plants are able to combat stress involving defense mechanism, resulting in healthy growth of the plants. The results are well coordinated as there is no change in the MDA content as compared to the plants grown on GS. In view of high Cr accumulation in edible part of S. oleracea grown on CS after irrigation with tap water, it is not advisable to use these plants for edible purposes. Summing up, it is recommended that the level of metals in the edible part should be checked instead of healthy growth as deciding parameter for consumption. It is demonstrated through this study that metal enriched plants have detoxification mechanism and grow well on organic matter enriched contaminated soil.     

Spatial distribution and seasonal variation of atmospheric bulk deposition of polycyclic aromatic hydrocarbons in Beijing-Tianjin region, North China

Bulk deposition samples were collected in remote, rural village and urban areas of Beijing-Tianjin region, North China in spring, summer, fall and winter from 2007 to 2008. The annually averaged PAHs concentration and deposition flux were 11.81 ± 4.61 μg/g and 5.2 ± 3.89 μg/m²/day respectively. PHE and FLA had the highest deposition flux, accounting for 35.3% and 20.7% of total deposition flux, respectively. More exposure risk from deposition existed in the fall for the local inhabitants. In addition, the PAHs deposition flux in rural villages (3.91 μg/m²/day) and urban areas (8.28 μg/m²/day) was 3.8 and 9.1 times higher than in background area (0.82 μg/m²/day), respectively. This spatial variation of deposition fluxes of PAHs was related to the PAHs emission sources, local population density and air concentration of PAHs, and the PAHs emission sources alone can explain 36%, 49%, 21% and 30% of the spatial variation in spring, summer, fall and winter, respectively.