Higgins A Z, Karlsson J O M
School of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331-2702, USA.
Cryobiology. 2008 Dec;57(3):223-33. doi: 10.1016/j.cryobiol.2008.09.001. Epub 2008 Sep 7.
We have investigated the confounding effects of dynamic range limitations on measurement of the osmotically inactive volume using electrical sensing zone instruments (e.g., Coulter counters), and propose an improved approach to parameter estimation. The conventional approach for analysis of cell size distributions measured by such particle sizing instruments requires data truncation: the mean cell volume is computed after exclusion of data below a specified lower bound (typically chosen to remove artifacts due to small-volume noise) and above an upper bound (typically governed by instrument limitations). The osmotically inactive volume is then estimated from a Boyle-van't Hoff plot of the averaged volume data obtained after exposure to various solution osmolalities. We demonstrate that systematic exclusion of data in the conventional approach introduces bias that results in erroneously high estimates of the osmotically inactive volume fraction. To minimize this source of error, we have devised a new algorithm based on fitting a bimodal distribution model to the non-truncated volume data. In experiments with mouse insulinoma (MIN6) cells, the osmotically inactive volume fraction was estimated to be 0.15+/-0.01 using the new method, which was significantly smaller than the estimate of 0.37+/-0.02 obtained using the conventional method (p<0.05). In silico experiments indicated that the parameter estimate obtained by the new method was accurate within 5%, whereas the error associated with the conventional approach was approximately 150%. Parametric analysis was used to elucidate the sensitivity of errors to variations in instrument dynamic range and cell volume distribution width.
我们研究了动态范围限制对使用电阻抗检测技术（如库尔特计数器）测量渗透惰性体积的混杂影响，并提出了一种改进的参数估计方法。分析此类粒度分析仪器测量的细胞大小分布的传统方法需要对数据进行截断：在排除低于指定下限（通常选择用于去除由于小体积噪声引起的伪像）和高于上限（通常由仪器限制决定）的数据后计算平均细胞体积。然后根据暴露于各种溶液渗透压后获得的平均体积数据的博伊尔 - 范特霍夫图来估计渗透惰性体积。我们证明，传统方法中系统地排除数据会引入偏差，导致对渗透惰性体积分数的估计错误地偏高。为了尽量减少这种误差来源，我们设计了一种新算法，该算法基于将双峰分布模型拟合到未截断的体积数据。在对小鼠胰岛素瘤（MIN6）细胞的实验中，使用新方法估计的渗透惰性体积分数为0.15±0.01，明显小于使用传统方法获得的0.37±0.02的估计值（p<0.05）。计算机模拟实验表明，新方法获得的参数估计在5%以内是准确的，而与传统方法相关的误差约为150%。使用参数分析来阐明误差对仪器动态范围和细胞体积分布宽度变化的敏感性。
