GIS-based multi-criteria evaluation for olive mill wastewater disposal site selection

Journal of Material Cycles and Waste Management - The installation of an olive mill wastewater (OMW) disposal site without well-defined standards and constraints may cause undesirable long-term...     

MicroRNAs’ role in the environment-related non-communicable diseases and link to multidrug resistance,regulation, or alteration

Environmental Science and Pollution Research - The discovery of microRNAs (miRNAs) 20 years ago has advocated a new era of “small molecular genetics.” About 2000 miRNAs are present that...     

The detoxifying effect of Polygonum equisetiforme extracts against dichlorvos (DDVP)-induced oxidative stress and neurotoxicity in the commercial clam Ruditapes decussatus

Environmental Science and Pollution Research - Effects of Polygonum equisetiforme extracts against dichlorvos were investigated in the commercial clam Ruditapes decussatus. The toxicity of this...     

Multiple biomarkers of pollution effects in Solea solea fish on the Tunisia coastline

This field study investigates the morphological indices (condition index, hepatosomatic index) and biochemical (catalase (CAT), glutathione S-transferase (GST), acetylcholinesterase (AChE), metallothionein (MT), lipid peroxidation) parameters in liver, gills and kidney of common sole (Solea solea) originating from different sites of the Tunisian coast area impacted by different anthropogenic activities. Differences among sites and tissues for AChE, GST, CAT, MT and TBARS were found and possibly related to known sources of domestic and industrial discharges in the studied sites. Liver, gills and kidney CAT, liver and kidney MT and brain AChE were key biomarkers to discriminate fish of different sites. So, we suggest using these biomarkers in future biomonitoring.     

Possible human health risk of some heavy metals from consumption of tilapia fish from Lake Mariut,Egypt

Environmental Science and Pollution Research - Lake Mariut Main Basin (MB) is not only one of the three basins composing Lake Mariut (LM) but is also the main source of the popular tilapia fish to...     

Efficacy and safety of doravirine in treatment-naive HIV-1-infected adults: a systematic review and meta-analysis

Environmental Science and Pollution Research - This research aims to study the safety and efficacy of doravirine in the treatment of HIV-1 (human immunodeficiency virus) patients. We conducted an...     

Artificial intelligence modeling to evaluate field performance of photocatalytic asphalt pavement for ambient air purification

In recent years, the application of titanium dioxide (TiO₂) as a photocatalyst in asphalt pavement has received considerable attention for purifying ambient air from traffic-emitted pollutants via photocatalytic processes. In order to control the increasing deterioration of ambient air quality, urgent and proper risk assessment tools are deemed necessary. However, in practice, monitoring all process parameters for various operating conditions is difficult due to the complex and non-linear nature of air pollution-based problems. Therefore, the development of models to predict air pollutant concentrations is very useful because it can provide early warnings to the population and also reduce the number of measuring sites. This study used artificial neural network (ANN) and neuro-fuzzy (NF) models to predict NO_x concentration in the air as a function of traffic count (T_r) and climatic conditions including humidity (H), temperature (T), solar radiation (S), and wind speed (W) before and after the application of TiO₂ on the pavement surface. These models are useful for modeling because of their ability to be trained using historical data and because of their capability for modeling highly non-linear relationships. To build these models, data were collected from a field study where an aqueous nano TiO₂ solution was sprayed on a 0.2-mile of asphalt pavement in Baton Rouge, LA. Results of this study showed that the NF model provided a better fitting to NO_x measurements than the ANN model in the training, validation, and test steps. Results of a parametric study indicated that traffic level, relative humidity, and solar radiation had the most influence on photocatalytic efficiency.     

In vitro biological activities and in vivo hepatoprotective role of brown algae-isolated fucoidans

Environmental Science and Pollution Research - Brown seaweeds are rich in polysaccharides, such as fucoidan (FUC) which has shown beneficial effects in several medical conditions. The aim of the...     

Ameliorative potential of manganese nanoparticles with low-level ionizing radiation against experimentally induced hepatocarcinogenesis

Environmental Science and Pollution Research - Nanotechnology is a rich field with infinite possibilities of drug designs for cancer treatment. We aimed to biosynthesize manganese nanoparticles (Mn...