20 resultados para Lines


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The possibility of printing two-dimensional micropatterns of biomolecule solutions is of great interest in many fields of research in biomedicine, from cell-growth and development studies to the investigation of the mechanisms of communication between cells. Although laser-induced forward transfer (LIFT) has been extensively used to print micrometric droplets of biological solutions, the fabrication of complex patterns depends on the feasibility of the technique to print micron-sized lines of aqueous solutions. In this study we investigate such a possibility through the analysis of the influence of droplet spacing of a water and glycerol solution on the morphology of the features printed by LIFT. We prove that it is indeed possible to print long and uniform continuous lines by controlling the overlap between adjacent droplets. We show how, depending on droplet spacing, several printed morphologies are generated, and we offer, in addition, a simple explanation of the observed behavior based on the jetting dynamics characteristic of the LIFT of liquids.

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Background: One of the problems in prostate cancer (CaP) treatment is the appearance of the multidrug resistance phenotype, in which ATP-binding cassette transporters such as multidrug resistance protein 1 (MRP1) play a role. Different localizations of the transporter have been reported, some of them related to the chemoresistant phenotype. Aim: This study aimed to compare the localization of MRP1 in three prostate cell lines (normal, androgen-sensitive, and androgen-independent) in order to understand its possible role in CaP chemoresistance. Methods: MRP1 and caveolae protein markers were detected using confocal microscopy, performing colocalization techniques. Lipid raft isolation made it possible to detect these proteins by Western blot analysis. Caveolae and prostasomes were identified by electron microscopy. Results: We show that MRP1 is found in lipid raft fractions of tumor cells and that the number of caveolae increases with malignancy acquisition. MRP1 is found not only in the plasma membrane associated with lipid rafts but also in cytoplasmic accumulations colocalizing with the prostasome markers Caveolin-1 and CD59, suggesting that in CaP cells, MRP1 is localized in prostasomes. Conclusion: We hypothesize that the presence of MRP1 in prostasomes could serve as a reservoir of MRP1; thus, taking advantage of the release of their content, MRP1 could be translocated to the plasma membrane contributing to the chemoresistant phenotype. The presence of MRP1 in prostasomes could serve as a predictor of malignancy in CaP

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Background: One of the problems in prostate cancer (CaP) treatment is the appearance of the multidrug resistance phenotype, in which ATP-binding cassette transporters such as multidrug resistance protein 1 (MRP1) play a role. Different localizations of the transporter have been reported, some of them related to the chemoresistant phenotype. Aim: This study aimed to compare the localization of MRP1 in three prostate cell lines (normal, androgen-sensitive, and androgen-independent) in order to understand its possible role in CaP chemoresistance. Methods: MRP1 and caveolae protein markers were detected using confocal microscopy, performing colocalization techniques. Lipid raft isolation made it possible to detect these proteins by Western blot analysis. Caveolae and prostasomes were identified by electron microscopy. Results: We show that MRP1 is found in lipid raft fractions of tumor cells and that the number of caveolae increases with malignancy acquisition. MRP1 is found not only in the plasma membrane associated with lipid rafts but also in cytoplasmic accumulations colocalizing with the prostasome markers Caveolin-1 and CD59, suggesting that in CaP cells, MRP1 is localized in prostasomes. Conclusion: We hypothesize that the presence of MRP1 in prostasomes could serve as a reservoir of MRP1; thus, taking advantage of the release of their content, MRP1 could be translocated to the plasma membrane contributing to the chemoresistant phenotype. The presence of MRP1 in prostasomes could serve as a predictor of malignancy in CaP

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Background: One of the problems in prostate cancer (CaP) treatment is the appearance of the multidrug resistance phenotype, in which ATP-binding cassette transporters such as multidrug resistance protein 1 (MRP1) play a role. Different localizations of the transporter have been reported, some of them related to the chemoresistant phenotype. Aim: This study aimed to compare the localization of MRP1 in three prostate cell lines (normal, androgen-sensitive, and androgen-independent) in order to understand its possible role in CaP chemoresistance. Methods: MRP1 and caveolae protein markers were detected using confocal microscopy, performing colocalization techniques. Lipid raft isolation made it possible to detect these proteins by Western blot analysis. Caveolae and prostasomes were identified by electron microscopy. Results: We show that MRP1 is found in lipid raft fractions of tumor cells and that the number of caveolae increases with malignancy acquisition. MRP1 is found not only in the plasma membrane associated with lipid rafts but also in cytoplasmic accumulations colocalizing with the prostasome markers Caveolin-1 and CD59, suggesting that in CaP cells, MRP1 is localized in prostasomes. Conclusion: We hypothesize that the presence of MRP1 in prostasomes could serve as a reservoir of MRP1; thus, taking advantage of the release of their content, MRP1 could be translocated to the plasma membrane contributing to the chemoresistant phenotype. The presence of MRP1 in prostasomes could serve as a predictor of malignancy in CaP

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In this paper we address the problem of extracting representative point samples from polygonal models. The goal of such a sampling algorithm is to find points that are evenly distributed. We propose star-discrepancy as a measure for sampling quality and propose new sampling methods based on global line distributions. We investigate several line generation algorithms including an efficient hardware-based sampling method. Our method contributes to the area of point-based graphics by extracting points that are more evenly distributed than by sampling with current algorithms