Parallel temperature-dependent microrheological measurements in a microfluidic chip

Josephson, Lilian Lam; Galush, William J.; Furst, Eric M.

doi:10.1063/1.4953863

Cited by 13 publications

(16 citation statements)

References 54 publications

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“…An inverted microscope (Axiovert 200; Carl Zeiss) equipped with fluorescent light and a high-speed camera was used to collect video images at 50 frames per second, of the Brownian motion of the probe particles at 63Â magnification. 49,53 A brightness-weighted centroid algorithm 51 was used to track the probe positions using the image stacks from the video microscopy in MATLAB (Mathworks Inc., Natick, MA). The displacement Dx of the probes was calculated as a function of lag time (t).…”

Section: Solution Viscositymentioning

confidence: 99%

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How Well Do Low- and High-Concentration Protein Interactions Predict Solution Viscosities of Monoclonal Antibodies?

Woldeyes

Wei

Razinkov

et al. 2019

Journal of Pharmaceutical Sciences

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Protein-protein interactions (PPI) and solution viscosities were measured at low and high protein concentrations under a range of formulation conditions for 4 different monoclonal antibodies. Static light scattering was used to quantify the osmotic second virial coefficient (B) and the zero-q limit static structure factor (S), versus protein concentration (c) from low to high c. Dynamic light scattering was used to measure the collective diffusion coefficient as a function of c and to determine the protein interaction parameter (k). Static light scattering and dynamic light scattering were combined to determine the hydrodynamic factor (H), which accounts for changes in hydrodynamic PPI as a function of c. The net PPI ranged from strongly repulsive to attractive interactions, via changes in buffer pH, ionic strength, and choice of monoclonal antibodies. Multiple-particle tracking microrheology and capillary viscometery were used to measure monoclonal antibodies solution viscosities under the same solution conditions. In most cases, even large and qualitative changes in PPI did not result in significant changes in protein solution viscosity. This highlights the complex nature of PPI and how they influence protein solution viscosity and raises questions as to the validity of using experimental PPI metrics such as k or B as predictors of high viscosity.

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Section: Solution Viscositymentioning

confidence: 99%

“…at lag times between 0.08 and 0.78 s. The optimal lag time was determined using the excess kurtosis and its Z-statistic parameter, as described previously. 49,53…”

Section: Solution Viscositymentioning

confidence: 99%

How Well Do Low- and High-Concentration Protein Interactions Predict Solution Viscosities of Monoclonal Antibodies?

Woldeyes

Wei

Razinkov

et al. 2019

Journal of Pharmaceutical Sciences

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“…Panorchan et al described a similar procedure for cross‐linking 3.4 kDa PEG to carboxylate‐modified 1 µm particles and found these to be less prone to particle–particle aggregation than amine‐ and carboxylate‐modified particles. Josephson et al used a grafting scheme consisting of N ‐hydroxysuccinimidyl ester–terminated 5 kDa PEG anchored to amine‐modified 1.0 m PS particles. These PEG‐stabilized particles were compared to the native amine particles in a combined antibody–surfactant system and showed a significant drop in particle aggregation except for some specific sample compositions where particle instability was observed.…”

Section: Introductionmentioning

confidence: 99%

Optical Microrheology of Protein Solutions Using Tailored Nanoparticles

Garting

Stradner

2018

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This work represents a critical re-examination of the application of dynamic light scattering (DLS)-based tracer particle microrheology to measure the zero shear viscosity of aqueous solutions of different proteins up to very high concentrations. It is demonstrated that a combination of surface-functionalized tracer particles, the use of the so-called 3D-DLS technique, and carefully chosen parameters for the scattering experiments is essential for a reliable and artifact-free determination of the viscosity of highly diverse protein solutions, while keeping the amount of protein to a minimum. The major challenges that arise in such microrheology experiments with protein solutions are discussed and used as guiding principles for the synthesis of all-purpose tracer particles with optimal size and an efficient surface functionalization, and the choice of the appropriate amount of tracers in the sample. Potential problems arising from depletion attractions between the tracer particles induced by the proteins are addressed, and compelling evidences for the absence of such effects are presented. The validity of the approach is corroborated by the perfect agreement between the zero shear viscosity obtained from 3D-DLS-based microrheology and literature data from classical rheological measurements for two vastly different protein-solvent systems up to concentrations close to the arrest transition.

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“…57 Likewise, parallelization can be achieved for rheological analysis of multiple samples. 58,59 Additional technological benefits include portability and disposability of devices, allowing point-of-care rheology. Microfluidic approaches to rheology thus offer several practical benefits, and one of the goals of this review is to highlight the degree to which different viscometric methods address these practical benefits.…”

Section: Technological Benefitsmentioning

confidence: 99%

Microfluidic viscometers for shear rheology of complex fluids and biofluids

2016

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The rich diversity of man-made complex fluids and naturally occurring biofluids is opening up new opportunities for investigating their flow behavior and characterizing their rheological properties. Steady shear viscosity is undoubtedly the most widely characterized material property of these fluids. Although widely adopted, macroscale rheometers are limited by sample volumes, access to high shear rates, hydrodynamic instabilities, and interfacial artifacts. Currently, microfluidic devices are capable of handling low sample volumes, providing precision control of flow and channel geometry, enabling a high degree of multiplexing and automation, and integrating flow visualization and optical techniques. These intrinsic advantages of microfluidics have made it especially suitable for the steady shear rheology of complex fluids. In this paper, we review the use of microfluidics for conducting shear viscometry of complex fluids and biofluids with a focus on viscosity curves as a function of shear rate. We discuss the physical principles underlying different microfluidic viscometers, their unique features and limits of operation. This compilation of technological options will potentially serve in promoting the benefits of microfluidic viscometry along with evincing further interest and research in this area. We intend that this review will aid researchers handling and studying complex fluids in selecting and adopting microfluidic viscometers based on their needs. We conclude with challenges and future directions in microfluidic rheometry of complex fluids and biofluids.

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Parallel temperature-dependent microrheological measurements in a microfluidic chip

Cited by 13 publications

References 54 publications

How Well Do Low- and High-Concentration Protein Interactions Predict Solution Viscosities of Monoclonal Antibodies?

How Well Do Low- and High-Concentration Protein Interactions Predict Solution Viscosities of Monoclonal Antibodies?

Optical Microrheology of Protein Solutions Using Tailored Nanoparticles

Microfluidic viscometers for shear rheology of complex fluids and biofluids

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