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Films of agarose enable rapid formation of giant liposomes in solutions of physiologic ionic strength.

ABSTRACT: This paper describes a method to form giant liposomes in solutions of physiologic ionic strength, such as phosphate buffered saline (PBS) or 150 mM KCl. Formation of these cell-sized liposomes proceeded from hybrid films of partially dried agarose and lipids. Hydrating the films of agarose and lipids in aqueous salt solutions resulted in swelling and partial dissolution of the hybrid films and in concomitant rapid formation of giant liposomes in high yield. This method did not require the presence of an electric field or specialized lipids; it generated giant liposomes from pure phosphatidylcholine lipids or from lipid mixtures that contained cholesterol or negatively charged lipids. Hybrid films of agarose and lipids even enabled the formation of giant liposomes in PBS from lipid compositions that are typically problematic for liposome formation, such as pure phosphatidylserine, pure phosphatidylglycerol, and asolectin. This paper discusses biophysical aspects of the formation of giant liposomes from hybrid films of agarose and lipids in comparison to established methods and shows that gentle hydration of hybrid films of agarose and lipids is a simple, rapid, and reproducible procedure to generate giant liposomes of various lipid compositions in solutions of physiologic ionic strength without the need for specialized equipment.

SUBMITTER: Horger KS

PROVIDER: S-EPMC2757642 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

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Films of agarose enable rapid formation of giant liposomes in solutions of physiologic ionic strength.

Horger Kim S KS Estes Daniel J DJ Capone Ricardo R Mayer Michael M

Journal of the American Chemical Society 20090201 5

This paper describes a method to form giant liposomes in solutions of physiologic ionic strength, such as phosphate buffered saline (PBS) or 150 mM KCl. Formation of these cell-sized liposomes proceeded from hybrid films of partially dried agarose and lipids. Hydrating the films of agarose and lipids in aqueous salt solutions resulted in swelling and partial dissolution of the hybrid films and in concomitant rapid formation of giant liposomes in high yield. This method did not require the presen ...[more]

PMID: 19154115

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Project description:Computational modelling of physical and biochemical processes has emerged as a means of evaluating medical devices, offering new insights that explain current performance, inform future designs and even enable personalized use. Yet resource limitations force one to compromise with reduced order computational models and idealized assumptions that yield either qualitative descriptions or approximate, quantitative solutions to problems of interest. Considering endovascular drug delivery as an exemplary scenario, we used a supervised machine learning framework to process data generated from low fidelity coarse meshes and predict high fidelity solutions on refined mesh configurations. We considered two models simulating drug delivery to the arterial wall: (i) two-dimensional drug-coated balloons and (ii) three-dimensional drug-eluting stents. Simulations were performed on computational mesh configurations of increasing density. Supervised learners based on Gaussian process modelling were constructed from combinations of coarse mesh setting solutions of drug concentrations and nearest neighbourhood distance information as inputs, and higher fidelity mesh solutions as outputs. These learners were then used as computationally inexpensive surrogates to extend predictions using low fidelity information to higher levels of mesh refinement. The cross-validated, supervised learner-based predictions improved fidelity as compared with computational simulations performed at coarse level meshes--a result consistent across all outputs and computational models considered. Supervised learning on coarse mesh solutions can augment traditional physics-based modelling of complex physiologic phenomena. By obtaining efficient solutions at a fraction of the computational cost, this framework has the potential to transform how modelling approaches can be applied in the evaluation of medical technologies and their real-time administration in an increasingly personalized fashion.

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Films of agarose enable rapid formation of giant liposomes in solutions of physiologic ionic strength.

Publications

Films of agarose enable rapid formation of giant liposomes in solutions of physiologic ionic strength.

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