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Updated: Jun 19, 2026

Measuring the Osmotic Water Permeability Coefficient (Pf) of Spherical Cells: Isolated Plant Protoplasts as an Example
Published on: October 8, 2014
Curve fitting approach for measurement of cellular osmotic properties by the electrical sensing zone method. II.
Adam Z Higgins1, Jens O M Karlsson
1School of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331-2702, USA.
Abstract:
In a companion paper, we demonstrated that dynamic range limitations can confound measurement of the osmotically inactive volume using electrical sensing zone instruments (e.g., Coulter counters), and presented an improved parameter estimation method in which a lognormal function was fit to the cell volume distribution to allow extrapolation beyond the bounds of the data. Presently, we have investigated the effect of dynamic range limitations on measurement of the cell membrane water permeability (L(p)), and adapted the lognormal extrapolation method for estimation of L(p) from transient volume data. An alternative strategy (the volume limit adjustment method, in which the measured isotonic volume distribution is used to generate model predictions for curve fitting, and the bounds of the dynamic range are adjusted such that extrapolation is not required) was also developed. The performance of these new algorithms was compared to that of a conventional parameter estimation method. The best-fit L(p) values from in vitro experiments with mouse insulinoma (MIN6) cells differed significantly for the different parameter estimation techniques (p<0.001). Using in silico experiments, the volume limit adjustment method was shown to be the most accurate (relative error 0.4+/-3.2%), whereas the conventional method underestimated L(p) by 19+/-2% for MIN6 cells. Parametric analysis revealed that the error associated with the conventional method was sensitive to the dynamic range and the width of the volume distribution. Our initial implementation of the lognormal extrapolation method also yielded significant errors, whereas accuracy of this algorithm improved after including a normalization scheme.
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