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- W2010674508 abstract "Gel electrophoresis (gel–EP) has been used for decades to separate charged biopolymers, such as DNA, RNA, and proteins, yet propagation of other charged colloidal objects, such as nanoparticles, during gel–EP has been studied comparatively little. Simply introducing anionic nanoparticles, such as sulfate–stabilized polystyrene nanospheres, in standard large-pore agarose gels commonly used for biomolecules does not automatically ensure propagation or size-separation because attractive interactions can exist between the gel and the nanoparticles. Whereas altering the surfaces of the nanoparticles is a possible solution, here, by contrast, we show that treating a common type I–A low-electroendoosmosis agarose gel with a passivation agent, such as poly-(ethyleneglycol), enables charged nanoparticles to propagate through large-pore passivated gels in a highly reproducible manner. Moreover, by taking advantage of the significant optical scattering from the nanoparticles, which is not easily measurable for biopolymers, relative to scattering from the gel, we perform real-time, light-scattering, video-tracking gel–EP. Continuous optical measurements of the propagation of bands of uniformly sized nanospheres in passivated gels provides the propagation distance, L, and velocity, v, as a function of time for different sphere radii, electric field strengths, gel concentrations, and passivation agent concentrations. The steady-state particle velocities vary linearly with applied electric field strength, E, for small E, but these velocities become non-linear for larger E, suggesting that strongly driven nanoparticles can become elastically trapped in the smaller pores of the gel, which act like blind holes, in a manner that thermal fluctuations cannot overcome. Based on this assumption, we introduce a simple model that fits the measured v(E) in both linear and non-linear regimes over a relevant range of applied voltages." @default.
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- W2010674508 date "2011-09-01" @default.
- W2010674508 modified "2023-10-03" @default.
- W2010674508 title "Software development for analyzing social interaction behaviors in mice using hidden Markov model" @default.
- W2010674508 doi "https://doi.org/10.1016/j.neures.2011.07.1698" @default.
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