Green Synthesis of Silver Nanoparticles Using Olea europaea Leaf Extract for Their Enhanced Antibacterial,Antioxidant, Cytotoxic and Biocompatibility Applications

Herein, we report the green synthesis of silver nanoparticles (OE-Ag NPs) by ecofriendly green processes using biological molecules of Olea europaea leaf extract. Green synthesized OE-Ag NPs were successfully characterized using different spectroscopic techniques. Antibacterial activity of OE-Ag NPs was assessed against four different bacteriological strains using the dilution serial method. The cytotoxic potential was determined against MCF-7 carcinoma cells using MTT assay in terms of cell viability percentage. Antioxidant properties were evaluated in terms of 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging. Biocompatibility was further examined by incubating the synthesized NPs with hMSC cells for 24 h. The results were demonstrated that synthesized OE-Ag NPs presented excellent log₁₀ reduction in the growth of all the tested bacterial strains, which as statistically equivalent (p > 0.05) to the standard antibiotic drug. Moreover, they also demonstrated excellent cytotoxic efficacy against the MCF-7 carcinoma cells compared to plant lead extract and Com-Ag NPs. Green synthesized OE-Ag NPs appeared more biocompatible to hMSC and 293T cells compared to Com-Ag NPs. Excellent biological results of the OE-Ag NPs might be attributed to the synergetic effect of NPs’ properties and the adsorbed secondary metabolites of plant leaf extract. Hence, this study suggests that synthesized OE-Ag NPs can be a potential contender for their various biological and nutraceutical applications. Moreover, this study will open a new avenue to produce biocompatible nanoparticles with additional biological functionalities from the plants.     

Prediction of Water Level using Monthly Lagged Data in Lake Urmia,Iran

Water Resources Management - Prediction of water level fluctuations in lakes is a necessary task in hydrological and limnological studies. Lake Urmia, a hyper-saline lake in the North Western part...     

3D culturing of human adipose-derived stem cells enhances their pluripotency and differentiation abilities

Human mesenchymal stem cells,such as human adipose-derived stem cells(hASCs),are typically cultured on a two-dimensional(2 D)monolayer material surface,on which 2 D culturing methods are easily performed and time-saving.However,hASCs usually suffer from decreased pluripotency and differentiation ability when cultured with a 2 D monolayer culturing method compared to hASCs cultured with a three-dimensional(3 D)culturing method,such as suspension culture.In this study,we evaluated whether the pluripotency and differentiation ability of hASCs can be reversibly changed during sequential cultivation with 2 D and 3 D culturing processes.The hASCs cultivated with a 3 D culturing process after 2 D culture showed at least 2-fold enhanced pluripotency(Sox2,Nanog,and OCT4)compared with that of hASCs cultured with the 2 D culture process alone.Furthermore,hASCs obtained from the 3 D culture process expressed increased levels of differentiation markers of chondrocytes and osteoblasts compared with hASCs obtained from the 2 D culture process when hASCs were induced to differentiate.However,their pluripotency and differentiation ability were extensively reduced when hASCs were shifted from 3 D culture to 2 D culture and vice versa,which indicates that hASCs show reversibility in terms of their pluripotency and differentiation ability depending on their environment in 2 D and 3 D culture.The reversibility of pluripotency and differentiation ability were found to last for at least 5 passages in culture during the alternative and sequential culture of cells with 2 D and 3 D culturing processes.Our study revealed the importance of the culture microenvironment in maintaining the pluripotency and differentiation ability of hASCs,which may reduce the effects of the aging process in hASCs.We discuss whether the environment of stem cell culture(i.e.,2 D or 3 D cultivation)can affect stem cell fate in terms of pluripotency and differentiation reversibility.     

Multi-objective sizing and topology optimization of truss structures using genetic programming based on a new adaptive mutant operator

Neural Computing and Applications - Most real-world engineering problems deal with multiple conflicting objectives simultaneously. In order to address this issue in truss optimization, this paper...     

The effects of fluoride on animals and plants in the South Safi zone

Fluride pollution caused by the factories processing natural phosphates 10 km south of Safi affects animals and plants. Fluoride concentrations are 4–10 times higher in contaminated plants than in plants from the non-polluted areas. Fluoride levels of 700 ppm, 280 ppm, 75 ppm, 25 ppm, and 1.6 ppm were found in grass, forage, straw, barley caryopses and drinking water, respectively. The ingestion of polluted plants and the inhalation of fluoride (as gases and dusts) induce a high daily intake in animals which show important signs and lesions of dental fluorosis. Serious toxicity signs were also observed in plants.     

Prediction of Daily Pan Evaporation using Wavelet Neural Networks

Prediction of daily evaporation has an important role in reservoir management, regional water planning and evaluation of drinking-water supplies. The main purpose of this study was to assess different types of mother wavelet as activation functions instead of commonly used sigmoid for finding the main differences in the results of daily pan evaporation prediction in the Lar synoptic station. So, using conjunction of wavelet theory and multilayer perceptron (MLP) network, two mother Wavelets named Mexican Hat and polyWOG1 are considered for developing hybrid WNNs. The algorithms were trained and tested using a 6-year data record (1999 daily values) from 2005/01/01 to 2010/09/01. Instead of using common sigmoid activation functions in MLP network, wavelet function was applied to construct the wavelet neural network. Results show that Mexican hat wavelet neural network in the best topology presents 98.35?% accuracy in training phase and 96.04?% in testing and PolyWOG1 wavelet neural network in the best topology presents 95.92?% accuracy in training phase and 91.03?% in testing of model. In the MLP model with standard sigmoid function results were 90.6?% in training and 87.63?% in testing. Comparison of WNN and MLP shows that Mexican hat mother wavelet could have better accuracy in the daily pan evaporation modeling.