Nanocarrier-mediated co-delivery systems for lung cancer therapy: recent developments and prospects

Environmental Chemistry Letters - Research has recently focused on combinational therapy using nanocarriers to overcome the obstacles associated with conventional therapy of lung cancer. The...     

Reservoir water quality: a case from Jordan

Jordan relies heavily on reservoirs building and development to cope with water supply challenges, where monitoring and assessment of reservoir water quality are critically important for the sustainable use of these water supplies. Mujib Dam is an important water supply source in central western Jordan. Evaluation of water quality parameters and their spatial distributions (vertical and horizontal) showed near-neutral pH values with nearly similar values from surface to bottom. The vertical profile of DO and TDS in the dammed reservoir showed slight decreasing trends with increasing depth. Although Ca, Mg, Na, and K concentrations varied slightly with depths, their variations showed no trends. Similarly, the vertical and horizontal distribution patterns of Cl, SO₄, HCO₃, NO₃, and PO₄ in Mujib reservoir water showed insignificant variations in surface water layer and relatively unchanged values or decreasing trends through the water column. Higher values of TN have been observed, especially in the western part, suggesting that agricultural activities and livestock farming in the upstream catchment are impacting water quality. Results revealed that weathering and dissolution of rocks are the major source of water chemistry. The majority of trace metal levels (Cd, Cr, Cu, Fe, Mn, Pb, Zn, Co, Ni, Sr, and B) in water showed relatively similar surface and bottom values. The concentrations of COD and BOD₅ in surface water were relatively low with higher concentrations observed in the northwestern corner, coincided with higher levels of chlorophyll a. The average ratio of TN to TP in surface water suggests that phosphorus is the limiting factor for the algal blooms, whereas the average chlorophyll a level in surface water indicates oligo-mesotrophic water.     

Impacts of and adaptation to climate change on the oil palm in Malaysia: a systematic review

Environmental Science and Pollution Research - The interaction and the interplay of climate change with oil palm production in the Southeast Asia region are of serious concern. This particularly...     

Could curcumin ameliorate titanium dioxide nanoparticles effect on the heart? A histopathological,immunohistochemical, and genotoxic study

Environmental Science and Pollution Research - The evaluation of the toxicological effects of titanium dioxide nanoparticles (TiO2NPs) is increasingly important due to their growing occupational...     

Polyphenolic extracts from the xerophyte Rhamnus lycioides as a radiation biodosimeter

The majority of dosimeters currently in use are synthetic and very expensive. Therefore, the study of the dosimetric characteristics of polyphenolic extracts of xerophytes is useful because drought stress causes an increase in the production of these cheap and natural compounds containing benzene rings. Here, the polyphenolic compounds were extracted from Rhamnus lycioides which was collected from Bou-Hedma National Park in Tunisia and identified using liquid chromatography-mass spectrometry (LC-MS). We investigated the impact of cobalt-60 (60Co) irradiation (0–30 kilogray (kGy)) on the color parameters of polyphenolic extracts of R. lycioides using the Konica Minolta CR 300 portable colorimeter and UV–Visible spectroscopy. The structural and morphological characteristics of the irradiated extracts were assessed using Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) technique and scanning electron microscopy (SEM). Overall, our results suggest that exposure to ionizing radiation (IR) of the polyphenolic components of the xerophyte R. lycioides has produced significant dose-dependent changes in their optical and morphological properties. Thus, these extracts can be valorized as biodosimeters in the dose range from 5 to 25 kGy.     

Magnetic nanoparticles incorporation into different substrates for dyes and heavy metals removal—A Review

Environmental Science and Pollution Research - Substantial discharge of hazardous substances, especially dyes and heavy metal ions to the environment, has become a global concern due to...     

Composting of municipal solid waste by different methods improved the growth of vegetables and reduced the health risks of cadmium and lead

Environmental Science and Pollution Research - Reutilization of putrescible municipal solid wastes (MSW) in agriculture can provide valuable plant nutrients. However, it may pose serious...     

Heavy-metal fractionation and distribution in soil profiles short-term-irrigated with sewage wastewater

Six soil profiles irrigated and non-irrigated with sewage wastewater were investigated for soil pH, electrical conductivity (EC), organic matter (OM), and CaCO₃. The distributions and chemical fractions of Cu, Zn, Cd, and Pb, and their lability were also studied. The results indicated that pH, EC, OM, and CaCO₃, as well as metal fractionation in soil profiles were affected by wastewater irrigation, especially in the surface layer. The surface layer (0-15 cm) irrigated with wastewater exhibited a 0.6 unit decrease in soil pH, a 40.6% decrease in CaCO₃, and a 200% increase in EC as compared with that of the non-irrigated soil. The soil OM increased from 0.04% to 0.35% in the surface layer. The irrigation of soil with wastewater resulted in transformation of metals from the carbonate fraction (CARB) towards the exchangeable (EXCH), Fe-Mn oxide (ERO), and organic (OM) fraction for Zn, towards the EXCH, the OM, and residual fraction for Cu, and towards the exchangeable (EXCH) fraction for Cd. It was concluded that the use of sewage wastewater led to salt accumulation and an increase in the readily labile fraction of Zn, Cu, and Cd in the surface layer. Therefore, this reason may limit the use of wastewater under arid and semi-arid conditions.     

Systematic development of an artificial neural network model for real-time prediction of ground-level ozone in Edmonton, Alberta, Canada

Ground-level ozone is a secondary pollutant that has recently gained notoriety for its detrimental effects on human and vegetation health. In this paper, a systematic approach is applied to develop artificial neural network (ANN) models for ground-level ozone (O3) prediction in Edmonton, Alberta, Canada, using ambient monitoring data for input. The intent of these models is to provide regulatory agencies with a tool for addressing data gaps in ambient monitoring information and predicting O3 events. The models are used to determine the meteorological conditions and precursors that most affect O3 concentrations. O3 time-series effects and the efficacy of the systematic approach are also assessed. The developed models showed good predictive success, with coefficient of multiple determination values ranging from 0.75 to 0.94 for forecasts up to 2 hr in advance. The inputs most important for O3 prediction were temperature and concentrations of nitric oxide, total hydrocarbons, sulfur dioxide, and nitrogen dioxide.