Use of HEPG2 cells to assay the safety of cosmetic active substances

The importance of this study is based on the need to obtain simple and efficient in vitro models to predict the in vivo toxicity of cosmetics, aiming not to use animals as experimental model. Here, we proposed the use of HepG2 cells, which are widely applied to simulate the hepatic function of the human organism in vitro. This cell line was chose since recent studies have shown that the liver is potentially the most frequently targeted organ by cosmetic ingredients, and beyond that, considering the widely application of in vitro assays to test the cutaneous permeation of cosmetic products, including the assays applying modified Franz cells, this technique becomes indispensable. Three different cosmetic active substances were used, and the toxicity to HepG2 cells was assessed by the MTT method. The treatment with hyaluronic acid showed no toxicity to HepG2 cells. Treating the cells with P. guajava L. extract were verified that increasing the amount of the extract in the media, the cellular viability decreased, and finally, the treatment of alpha-lipoic acid showed a cytoprotective effect in relation to the treatment with propylene glycol. The study demonstrated the suitability in using HepG2 cells to assess the safety of cosmetic active substances, helping in the prediction of if the substance could be hepatotoxic if could reach the bloodstream

Use of uniform designs in combination with neural networks for viral infection process development

This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), times of infection, and harvest (24, 48, 72 hours) and the monitored output parameter was viral production. A multilevel factorial experimental design was performed for the study of this system. Fractions of this experimental approach (18, 24, 30, 36 and 42 runs), defined according uniform designs, were used as alternative for modelling through artificial neural network and thereafter an output variable optimization was carried out by means of genetic algorithm methodology. Model prediction capacities for all uniform design approaches under study were better than that found for classical factorial design approach. It was demonstrated that uniform design in combination with artificial neural network could be an efficient experimental approach for modelling complex bioprocess like viral production. For the present study case, 67% of experimental resources were saved when compared to a classical factorial design approach. In the near future, this strategy could replace the established factorial designs used in the bioprocess development activities performed within biopharmaceutical organizations because of the improvements gained in the economics of experimentation that do not sacrifice the quality of decisions.

Potential use of polyacrylamide for soil erosion control in Brazil

Since soil erosion is currently a worldwide threat, its control has become a necessity. The performance and effectiveness of synthetic organic polymers such polyacrylamide (PAM), have been intensively studied, especially for erosion control in temperate climate conditions. In tropical regions, however, where climatic conditions are usually severe, very little research has been conducted. The Brazilian region is a good example, where few papers on this subject exist. In addition to the severe climatic conditions, careless land use has been prevalent for many years. The use of PAM for erosion control in Brazilian soils may be a good option to minimize the impacts of the soil degradation process, but more research is required to optimize its application.