Dendrimer nanocarriers for transport modulation across models of the pulmonary epithelium

The purpose of this study was to determine the effect of PEGylation on the interaction of poly(amidoamine) (PAMAM) dendrimer nanocarriers (DNCs) with in vitro and in vivo models of the pulmonary epithelium. Generation-3 PAMAM dendrimers with varying surface densities of PEG 1000 Da were synthesized and characterized. The results revealed that the apical to basolateral transport of DNCs across polarized Calu-3 monolayers increases with an increase in PEG surface density. DNC having the greatest number of PEG groups (n = 25) on their surface traversed at a rate 10-fold greater than its non-PEGylated counterpart, in spite of their larger size. This behavior was attributed to a significant reduction in charge density upon PEGylation. We also observed that PEGylation can be used to modulate cellular internalization. The total uptake of PEG-free DNC into polarized Calu-3 monolayers was 12% (w/w) vs 2% (w/w) for that with 25 PEGs. Polarization is also shown to be of great relevance in studying this in vitro model of the lung epithelium. The rate of absorption of DNCs administered to mice lungs increased dramatically when conjugated with 25 PEG groups, thus supporting the in vitro results. The exposure obtained for the DNC with 25PEG was determined to be very high, with peak plasma concentrations reaching 5 mu gmL(-1) within 3 h. The combined in vitro and in vivo results shown here demonstrate that PEGylation can be potentially used to modulate the internalization and transport of DNCs across the pulmonary epithelium. Modified dendrimers thereby may serve as a valuable platform that can be tailored to target the lung tissue for treating local diseases, or the circulation, using the lung as pathway to the bloodstream, for systemic delivery.

Electrical transport mechanisms and structure of hydrogenated and non-hydrogenated nanocrystalline Ga1-xMnxAs films

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.