TY - JOUR
KW - Biophysics
KW - Cell biology
KW - Computational biology and bioinformatics
KW - Neuroscience
AU - Davide Ortolan
AU - Pushkar Sathe
AU - Andrei Volkov
AU - Dominik Reichert
AU - Sheldon Sebastian
AU - Arvydas Maminishkis
AU - Nicholas J. Schaub
AU - Bengt Ljungquist
AU - Devika Bose
AU - Jorge Ferrari
AU - Nyusha Lin
AU - Gianluca Pegoraro
AU - Carl G. Simon
AU - Ruchi Sharma
AU - Peter Bajcsy
AU - Kapil Bharti
AB - The retinal pigment epithelium (RPE) is a specialized cell monolayer that forms the barrier between the subretinal and choroidal spaces. During development, RPE cells polarize perpendicular to the monolayer plane such that organelles attain specific intracellular locations. This allows the RPE to differentially interact with overlying photoreceptors and underlying choriocapillaris. When RPE polarity is disrupted, tissue homeostasis is disturbed, leading to retinal degeneration. The subcellular organizational principles of RPE polarity are unknown. We developed an artificial intelligence (AI), specifically a mask region-based convolutional neural network-assisted high-content image analysis platform combined with mathematical modeling to develop a quantitative three-dimensional digital twin of RPE subcellular structures during the establishment of apical/basal polarity, polarity organization with learning-based analysis for RPE image segmentation (POLARIS). We discovered, during apical/basal polarization, cells constrict along the lateral axis and elongate apically, nuclear volume decreases, nuclear envelope develops invaginations, junctional complexes consolidate to the lateral membrane, the endoplasmic reticulum and mitochondria increase in volume and translocate towards the nucleus, and lysosomes move towards the central-apical side. AI algorithm and mathematical analysis reveal non-stochastic cell state transitions and organelle interactions in 3D during RPE polarization. These integrated AI-based quantitative data provide a reference digital twin to discover intracellular defects in diseased RPE.
BT - npj Artificial Intelligence
DA - 2026-02-06
DO - 10.1038/s44387-026-00074-6
IS - 1
LA - en
N2 - The retinal pigment epithelium (RPE) is a specialized cell monolayer that forms the barrier between the subretinal and choroidal spaces. During development, RPE cells polarize perpendicular to the monolayer plane such that organelles attain specific intracellular locations. This allows the RPE to differentially interact with overlying photoreceptors and underlying choriocapillaris. When RPE polarity is disrupted, tissue homeostasis is disturbed, leading to retinal degeneration. The subcellular organizational principles of RPE polarity are unknown. We developed an artificial intelligence (AI), specifically a mask region-based convolutional neural network-assisted high-content image analysis platform combined with mathematical modeling to develop a quantitative three-dimensional digital twin of RPE subcellular structures during the establishment of apical/basal polarity, polarity organization with learning-based analysis for RPE image segmentation (POLARIS). We discovered, during apical/basal polarization, cells constrict along the lateral axis and elongate apically, nuclear volume decreases, nuclear envelope develops invaginations, junctional complexes consolidate to the lateral membrane, the endoplasmic reticulum and mitochondria increase in volume and translocate towards the nucleus, and lysosomes move towards the central-apical side. AI algorithm and mathematical analysis reveal non-stochastic cell state transitions and organelle interactions in 3D during RPE polarization. These integrated AI-based quantitative data provide a reference digital twin to discover intracellular defects in diseased RPE.
PY - 2026
EP - 20
T2 - npj Artificial Intelligence
TI - AI driven 3D subcellular RPE map discovers cell state transitions in establishment of apical-basal polarity
UR - https://www.nature.com/articles/s44387-026-00074-6
VL - 2
Y2 - 2026-03-05
SN - 3005-1460
ER -