2 resultados para Rising, Oliver
em Repositório da Produção Científica e Intelectual da Unicamp
Resumo:
Silver nanoparticles have attracted considerable attention due to their beneficial properties. But toxicity issues associated with them are also rising. The reports in the past suggested health hazards of silver nanoparticles at the cellular, molecular, or whole organismal level in eukaryotes. Whereas, there is also need to examine the exposure effects of silver nanoparticle to the microbes, which are beneficial to humans as well as environment. The available literature suggests the harmful effects of physically and chemically synthesised silver nanoparticles. The toxicity of biogenically synthesized nanoparticles has been less studied than physically and chemically synthesised nanoparticles. Hence, there is a greater need to study the toxic effects of biologically synthesised silver nanoparticles in general and mycosynthesized nanoparticles in particular. In the present study, attempts have been made to assess the risk associated with the exposure of mycosynthesized silver nanoparticles on a beneficial soil microbe Pseudomonas putida. KT2440. The study demonstrates mycosynthesis of silver nanoparticles and their characterisation by UV-vis spectrophotometry, FTIR, X-ray diffraction, nanosight LM20 - a particle size distribution analyzer and TEM. Silver nanoparticles obtained herein were found to exert the hazardous effect at the concentration of 0.4μg/ml, which warrants further detailed investigations concerning toxicity.
Resumo:
There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.