## 3 Results
### Comparing GLIE Fluctuations in Live Jurkat and Primary T Cells
This neutralization procedure is based on first determining the regression function in primary T cells for these two parameters from the average gray level. Then,  
Figure 10: The correlations between average gray level, average GLIE and \(a\) parameters in primary T cells (n = 219) and in Jurkat cells (n = 161). The correlation between average gray level and average GLIE values in primary T cells (**a**) and in Jurkat cells (**b**). The correlation between average GLIE values and \(a\) parameter in primary T cells (**c**) and in Jurkat cells (**d**). The correlation between average gray level values and \(a\) parameter in primary T cells (**e**) and in Jurkat cells (**f**). The linear regression formulas are presented in panels **a**,**e**. R- and _p_-values of each correlation are presented. we calculate the difference between the measured value of the parameter and its predicted value according to the regression function. Figure 11: Adjusting for the influence of average gray level on the average GLIE and \(a\) parameters values. (**a**) Average GLIE values according to the average gray level in primary T cells and Jurkat cells. The linear regression line for that correlation in primary T cells is presented (that linear regression equation is also presented in Figure 10a). Relating to this linear regression, an example of adjusted GLIE parameter value which is calculated from the difference between the measured average GLIE value and the expected value from the linear regression function is presented. (**b**) Parameter \(a\) values according to the average gray level in primary T cells and Jurkat cells. The linear regression line for that correlation in primary T cells is presented (that linear regression equation is also presented in Figure 10e). Relating to this linear regression, an example of adjusted \(a\) parameter value, which is calculated from the difference between the measured \(a\) parameter value and the expected value from the linear regression function, is presented. Calculating the adjusted \(a\) parameter (_adj. a_) and other GLIE fluctuation parameters (_b_, _SSE_ and _SA_) in primary T cells and in Jurkat malignant cells reveals that the values of these parameters are much higher in malignant cells (as shown in Figure 12). On the other hand, adjusted average GLIE values were lower in the malignant cells. The higher mechanical work and dynamics in malignant cells probably resulted in more intracellular homogeneity, lower adjusted GLIE (_adj._ GLIE) values and higher GLIE fluctuation parameters: _adj. a_, \(b\), _SSE_ and _SA_. Differences in structural parameters or insufficient normalization of different light intensities may also influence the adjusted average GLIE values. When analyzing the difference between primary T lymphocytes and Jurkat cells according to the corresponding SICS analysis parameters, the obtained results are less consistent. As can be seen in Figure 13, while \(b\) parameter is significantly higher in Jurkat cells, all other parameters (namely \(a\), _SSE_ and _SA_) are all lower in these cells. Figure 12: GLIE fluctuation parameters values in primary T cells (n = 219), in comparison to Jurkat cells (n = 161). parameter _adj. a_ values (**a**) or parameter \(b\) values (**b**) or parameter _SSE_ values (**c**) or parameter _SA_ values (**d**) or parameter _adj._ GLIE values (**e**) in primary T cells vs. Jurkat cells. Error bars in panels **a–e** are SEM, and _p_-values are presented in the corresponding panels. Utilizing GLIE or SICS parameters may enable an accurate differentiation between primary T cells and malignant (Jurkat) T cells on the basis of multiple, single cell examinations. When analyzed by a binary logistic regression, we found a discrimination power or AUC (Area Under Receiver-Operating-Characteristic (ROC) Curve) of 0.92 for GLIE parameters and 0.86 for SICS parameters (see ROC curve in Figure 13e). The percentage of correct classifications was 86% for GLIE parameters and 78% for SICS parameters (with a classification cutoff of 0.5).