Photocatalytic and Cytotoxic Effects of Nitrogen-Doped TiO2 Nanoparticles on Melanoma Cells.

Titanium dioxide (TiO2) has attracted attention as a photosensitizer in the field of photodynamic therapy (PDT) due to its low toxicity and high photostability. In the present work, nitrogen-doped TiO2 (N-TiO2) nanoparticles had their photokilling efficiency evaluated on a murine melanoma cell line (B16-F10) and fibroblasts (NIH 3T3). The N-TiO2 nanoparticles were prepared by a modified hydrogen peroxide sol-gel process using triethylamine as nitrogen precursor. XRD measurements showed that all TiO2 and N-TiO2 samples consisted of an anatase crystalline phase and no trace of rutile was detected. N-TiO2 nanoparticles showed higher absorbance in the visible region than pure TiO2. Nanoparticle dosage increase from 0.1 mg/ml to 0.5 mg/ml played a role in cell viability, causing high cytotoxicity in melanoma and fibroblast cells. The cytotoxic potential of N-TiO2 on cells was analyzed using visible light, UV-A irradiation and dark conditions. All samples were cytotoxic in a PDT test, and N-TiO2 caused 93% death in melanoma cells under UV irradiation treatment at 0.5 mg/ml. Gene expression analysis of this sample showed, under ultraviolet photoexcitation, an increase of pro-apoptotic BAX gene expression, suggesting cell death by apoptosis.

Solid phase extraction of petroleum carboxylic acids using a functionalized alumina as stationary phase.

Petroleum essentially consists of a mixture of organic compounds, mainly containing carbon and hydrogen, and, in minor quantities, compounds with nitrogen, sulphur, and oxygen. Some of these compounds, such as naphthenic acids, can cause corrosion in pipes and equipment used in processing plants. Considering that the methods of separation or clean up the target compounds in low concentrations and in complex matrix use large amounts of solvents or stationary phases, is necessary to study new methodologies that consume smaller amounts of solvent and stationary phases to identify the acid components present in complex matrix, such as crude oil samples. The proposed study aimed to recover acid compounds using the solid phase extraction method, employing different types of commercial stationary ion exchange phases (SAX and NH(2)) and new phase alumina functionalized with 1,4-bis(n-propyl)diazoniabicyclo[2.2.2]octane chloride silsesquioxane (Dab-Al(2)O(3)), synthesized in this work. Carboxylic acids were used as standard mixture in the solid phase extraction for further calculation of recovery yield. Then, the real sample (petroleum) was fractionated into saturates, aromatics, resins, and asphaltenes, and the resin fraction of petroleum (B1) was eluted through stationary ion exchange phases. The stationary phase synthesized in this work showed an efficiency of ion exchange comparable to that of the commercial stationary phases.

Fungal biosynthesis of lignin-modifying enzymes from pulp wash and Luffa cylindrica for azo dye RB5 biodecolorization using modeling by response surface methodology and artificial neural network.

This study demonstrates the evaluation between the artificial neural network technique coupled to the genetic algorithm (ANN-GA) and the response surface methodology (RSM) for prediction of Reactive Black 5 (RB5) decolorization by crude enzyme from Pleurotus. sajor-caju. Fungal lignin-modifying enzymes (FLME) were synthesized using pulp wash (PW) as an inducing substrate, and L. cylindrica (L.C) for cell immobilization. When grown in PW, the fungus showed higher Lac activity (126.5 IU. mL-1), whereas when immobilized a higher MnP activity was achieved (22.79 IU. mL-1), but both methods were capable of decolorizing the dye in about 89.4 % and 75 %, respectively. This indicates applicability of PW as an alternative substrate for FLME induction and viability of immobilization for MnP synthesis. For RB5 decolorization, the action of the crude enzyme extract was considered as a function of pH, dye concentration, temperature, and reaction time. The models are well adjusted to predict the efficiency of biodecolorization, with no statistical difference between ANN-GA and RSM, which indicates potential for green enzymes prospecting application in bioprocess industry.