Figure 4.

Automatic classification of the caging events. (a) Moving from upper plots to lower ones, in the top row, three archetypal evolutions of pH vs time are shown (mimicking, respectively, an outer, an uptake, and an inner event). In the successive line, this dynamical information is converted into static histograms: crucially, while caging is coupled with a bimodal distribution, outer and inner events (obviously) result in monomodal distribution, and this observation is the core of the automatic classification. In the third row, we dissect the obtained distributions in terms of 10 quartiles: this allows for PCA over the latter. Finally, in the bottom row, we have a phase diagram where this classification naturally shines in the plane of the first two principal components. (b) Decomposition of the two principal components in terms of the original quantiles. (c) Cluster’s emergence (by automatic detection) of the various events on the datasets reported for both the cellular lines.