Optimization of Xanthan Gum/Poly(acrylic acid)/Cloisite 15A Semi-IPN Hydrogels for Heavy Metals Removal

Journal of Polymers and the Environment - Semi-interpenetrating networks (semi-IPNs) of Xanthan gum/poly (acrylic acid) containing Cloisite 15A were prepared via radical polymerization using a...     

In Vitro and In Vivo Anticancer Activity of Ferula Gummosa Essential Oil Nanoemulsions (FGEO-NE) for the Colon Cancer Treatment

This survey was performed to aim of synthesize Nano emulsion from Ferula gummosa essential oil (FEGO-NE) and to evaluate its anti-tumor effect. First, Ferula gummosa essential oil was analyzed by GC–MS method, and then the Nano emulsion was synthesized as O/W and after characterization by DLS, Zeta potential, AFM, FESEM and TEM methods, its toxicity was evaluated by MTT method. Then its pro-apoptotic effects were evaluated by qPCR (Caspase3, 9, Bax and Bcl-2) method and AO/PI staining. The cancer induction model was used to evaluate the antitumor effects in Balb/C mice. The anti-angiogenic and antioxidant effects were evaluated by qPCR (VEGF, CAT and SOD) method. The results of physicochemical studies showed the formation of droplet with dimensions of 24.6 nm, dispersion index of 0.41 and zeta potential of ? 28.5 mV with a spherical morphology. The Nano emulsion synthesized at a concentration of 2.9 μg/mL inhibited about 50% of ht-29 cells, while up to a concentration of 4 μg/mL showed no inhibitory effect on normal cells. Increase of caspase 3, 9 and Bax and decrease of BCL-2 gene expression along with increase of apoptotic cells in AP/PI staining confirmed induction of apoptosis by FEGO-NE. The FEGO-NE showed an inhibitory effect on angiogenesis and an additive effect on the expression of antioxidant genes. In addition, the reduction of tumor volume (69.72% in 14 days) in samples treated with FEGO-NE was confirmed. The results of this study showed that FEGO-NE by various mechanisms are able to inhibit cancer cells and have a reducing effect on induced tumors in the in vivo model. These results suggest FEGO-NEs as a suitable candidate for cancer therapy studies.

     

The long-term effect of exposure to respirable particulate matter on the incidence of myocardial infarction: a systematic review and meta-analysis study

Environmental Science and Pollution Research - Although several studies have investigated the long-term association of respirable particulate matter (PM?≤?10 µm)...     

Synthesis of magnetic nanoparticles and their effects on growth and physiological parameters of Calotropis procera seedlings

Environmental Science and Pollution Research - The present study was carried out to elucidate effects of synthesized magnetic nanoparticles (MNPs) on morphological and physiological parameters and...     

Land cover mapping based on random forest classification of multitemporal spectral and thermal images

Thematic mapping of complex landscapes, with various phenological patterns from satellite imagery, is a particularly challenging task. However, supplementary information, such as multitemporal data and/or land surface temperature (LST), has the potential to improve the land cover classification accuracy and efficiency. In this paper, in order to map land covers, we evaluated the potential of multitemporal Landsat 8’s spectral and thermal imageries using a random forest (RF) classifier. We used a grid search approach based on the out-of-bag (OOB) estimate of error to optimize the RF parameters. Four different scenarios were considered in this research: (1) RF classification of multitemporal spectral images, (2) RF classification of multitemporal LST images, (3) RF classification of all multitemporal LST and spectral images, and (4) RF classification of selected important or optimum features. The study area in this research was Naghadeh city and its surrounding region, located in West Azerbaijan Province, northwest of Iran. The overall accuracies of first, second, third, and fourth scenarios were equal to 86.48, 82.26, 90.63, and 91.82 %, respectively. The quantitative assessments of the results demonstrated that the most important or optimum features increase the class separability, while the spectral and thermal features produced a more moderate increase in the land cover mapping accuracy. In addition, the contribution of the multitemporal thermal information led to a considerable increase in the user and producer accuracies of classes with a rapid temporal change behavior, such as crops and vegetation.     

A Novel Approach to Biological Treatment of Contaminated Water

Over the past few years, the focus of our research has been to respond to the recognized needs for novel biological processes that are capable of destroying a wide range of biodegradable pollutants and providing the perfect environment for complex interspecies interactions required for the degradation of environmental contaminants. A new biotechnology process called Biological Permeable Barrier (BPB) was developed to provide high microbial density, stable environmental conditions, and protective measures for microbial activities for in‐situ bioremediation of contaminated groundwater. This patented technology (U.S. Patent 6,337,019 ) is based on the creation of a structured matrix, or Bio‐beads, that provides the perfect environment for organic‐degrading microorganisms to establish biofilms capable of destroying the contaminants in water with remarkable stability and control. For over 240 days, the viability and performance of the BPB (Bio‐beads) system were shown for biodegradation of a targeted contaminant, 2,4,6‐ trichlorophenol (TCP), under a variety of operating and stress conditions (Razavi‐Shirazi, 1997 ). Extensive batch experiments were also conducted to obtain necessary data to determine the rate of TCP diffusion into the Bio‐beads, adsorption properties of the Bio‐beads, and substrate‐use rate of the mixed bioculture as free cells and as immobilized cells (Bio‐beads). A simulated model of BPB was also characterized with its porosity, permeability, and compressibility or deformation under typical field conditions. Our extensive research showed that BPB takes advantage of a controlled biotechnology process to overcome the disadvantages and uncertainties associated with conventional biological processes. A summary of our investigation is presented here. © 2002 Wiley Periodicals, Inc.     

Managing uncertainties through scenario analysis in strategic environmental assessment

Planning for the future is uncertain, and scenario analysis is a method of coping with the uncertainties of future plans. This paper addresses how to deal with future uncertainties by using scenario analysis as a possible approach for conducting a strategic environmental assessment (SEA). Although scenario-based approaches have been linked to strategic planning and SEA, this paper for the first time proposes how a combined approach may be implemented using specific tools and methodologies and, further on, it also implements the first three stages of the six stages proposed for the ‘scenario-based strategic planning’ approach. This work is an attempt to standardize SEA and scenario analysis as a combined approach. The three stages are tested within the Tourism Development Plan of the Iranian province of Gilan, which has been selected as a case study.     

Spatial analysis of chromium in southwestern part of Iran: probabilistic health risk and multivariate global sensitivity analysis

This study was concerned with chromium as a potential carcinogenic contaminant in 64 wells located in five aquifers, southwest of Iran. A probabilistic health risk assessment indicated a high risk to the local residents including adults and children in the study area. A sequential sensitivity analysis and a novel approach known as multivariate global sensitivity analysis using both principal component analysis and B-spline were applied to investigate the behavior of health risk model along time considering four independent input parameters in the risk equation. In this context, based on the results of sensitivity analysis, concentration of chromium in drinking water (C_w) and body weight (W) were the most influential parameters. Random forest (RF) was used as a variable selection method to choose the most influential parameters for the prediction of chromium. Five parameters, among 13 water quality variables, including phosphate, nitrate, fluoride, manganese and iron were selected by RF as the most important parameters for spatial prediction. Hybrid methods of RF and ordinary kriging (RFOK) and RF and inverse distance weighting (RFIDW) were then applied for spatial prediction of Cr using the secondary variables. The RFOK and RFIDW were more efficient than that of ordinary kriging (OK) with respect to a cross-validation algorithm. For instance, in terms of relative root mean squared error, the performance of OK was improved from 31.72 to 23.21 and 23.61 for RFOK and RFIDW, respectively.

     

Plants growing in a mining area: screening for metal accumulator plants possibly useful for bioremediation

A field study was conducted in an iron mine in Hamedan (Iran) to find native accumulator plants and to evaluate the extent of metal bioaccumulation in the naturally growing vegetation. The concentrations of total As, Cd, Cr, Fe, Mn, Mo, Ni, Pb, Si, and Zn were found to be higher in the mine than in soil. These plants accumulated the highest amounts of the following metals in their roots: Euphorbia cheiradenia As, Stipa barbata Cd, Pb and Cr, Euphorbia macroclada Cu, Centaurea iberica Fe, Reseda lutea Mo, Salvia spinosa Ni and Zn, and Xanthium strumarium Se. In the aerial parts, the highest metal accumulation was found in Epilobium fragilis As, Carthamus oxyacantha Cd, Fe, Mn, and Pb, Verbascum speciosum Cu, Centaurea iberica Mo, Salvia spinosa Ni and Cr, Glaucium grandiflorum Se, and Malva neglecta Zn. Enrichment factors and bioconcentration factors were also determined; C. oxyacantha, S. spinosa, M. neglecta, C. iberica, V. speciosum, G. grandiflorum, and E. fragilis are the most effective accumulators and are proposed for phytoremediation of polluted soils.