Fig. 2: Mapping of cell borders and nuclei. | npj Artificial Intelligence

Fig. 2: Mapping of cell borders and nuclei.

From: AI driven 3D subcellular RPE map discovers cell state transitions in establishment of apical-basal polarity

Fig. 2: Mapping of cell borders and nuclei.The alternative text for this image may have been generated using AI.

A Representative 3D reconstruction of iRPE cells treated with PGE2 or HPI4 at each week of maturation (magenta = phalloidin, cyan = Hoechst; scale bar = 5 μm). B Integrated reference maps showing cells and nuclei dimensions and their relative location for each condition. The average cell and nucleus dimensions (height along the Z axis, and half of the average between minimum and maximum Feret’s diameters from images projected along the Z axis) were calculated from the entire dataset (16 cell lines, 30 FOVs per condition). Half-cell and half-nucleus are displayed as organelles location calculated in the subsequent figures, which was measured using absolute distances from the cell membrane or centroid. The location of the nucleus was calculated as the average distance between the cell and nucleus centroids along the Z axis and the X/Y plane. The black rectangles represent the average cell dimensions, while the surrounding gray bands represent the confidence interval estimated using two standard deviations from the average cell dimensions (95% of the data). The average nucleus and its confidence interval are shown in yellow. C Raincloud plots depicting the changes over time and between treatments for cells (top) and nuclei (bottom) cross-sectional area, aspect ratio, and volume (the points indicate the average values for each FOV; the diamonds represent the median, and the error bars indicate the 5th and 95th percentiles. Two-sided Welch’s t-test was performed to compare PGE2- and HPI4-treated cells at each timepoint. N = 30; ***P < 0.005, *P < 0.05). The solid lines indicate the generalized linear model maximum likelihood fit for the two treatments with week and the square of week as dependent variables.

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