RESUMO
Magnetic drug targeting (MDT) improves the integrity of healthy tissues and cells during treatment with cytotoxic drugs. An anticancer drug is bound to superparamagnetic iron oxide nanoparticles (SPION), injected into the vascular supply of the tumor and directed into the tumor by means of an external magnetic field. In this study, we investigated the impact of SPION, mitoxantrone (MTO) and SPIONMTO on cell viability in vitro and the nonspecific uptake of MTO into circulating leukocytes in vivo. MDT was compared with conventional chemotherapy. MTO uptake and the impact on cell viability were assessed by flow cytometry in a Jurkat cell culture. In order to analyze MTO loading of circulating leukocytes in vivo, we treated tumor-bearing rabbits with MDT and conventional chemotherapy. In vitro experiments showed a dose-dependent MTO uptake and reduction in the viability and proliferation of Jurkat cells. MTO and SPIONMTO showed similar cytotoxic activity. Non-loaded SPION did not have any effect on cell viability in the concentrations tested. Compared with systemic administration in vivo, MDT employing SPIONMTO significantly decreased the chemotherapeutic load in circulating leukocytes. We demonstrated that MDT spares the immune system in comparison with conventional chemotherapy.
Assuntos
Proliferação de Células/efeitos dos fármacos , Citotoxinas , Sistemas de Liberação de Medicamentos/métodos , Leucócitos/metabolismo , Campos Magnéticos , Nanopartículas de Magnetita/química , Neoplasias Experimentais , Animais , Citotoxinas/química , Citotoxinas/farmacologia , Feminino , Humanos , Células Jurkat , Leucócitos/patologia , Neoplasias Experimentais/tratamento farmacológico , Neoplasias Experimentais/metabolismo , Neoplasias Experimentais/patologia , CoelhosRESUMO
Most of the functional RNA elements located within large transcripts are local. Local folding therefore serves a practically useful approximation to global structure prediction. Due to the sensitivity of RNA secondary structure prediction to the exact definition of sequence ends, accuracy can be increased by averaging local structure predictions over multiple, overlapping sequence windows. These averages can be computed efficiently by dynamic programming. Here we revisit the local folding problem, present a concise mathematical formalization that generalizes previous approaches and show that correct Boltzmann samples can be obtained by local stochastic backtracing in McCaskill's algorithms but not from local folding recursions. Corresponding new features are implemented in the ViennaRNA package to improve the support of local folding. Applications include the computation of maximum expected accuracy structures from RNAplfold data and a mutual information measure to quantify the sensitivity of individual sequence positions.