New Platform Detects Vesicle Exocytosis with Deep Learning

Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis

A team of international scientists has unveiled a powerful new deep-learning platform that automates the detection and analysis of vesicle exocytosis, one of the most dynamic and essential processes in cell biology. The tool, called IVEA (Intelligent Vesicle Exocytosis Analysis), promises to transform how researchers study cellular communication, hormone release, and immune responses.

Exocytosis is the process by which cells release substances like neurotransmitters or hormones. Traditionally, analyzing these events in live-cell imaging has been a painstaking, manual task. But IVEA changes that.

The platform is 60 times faster than manual analysis, and its modular design allows researchers to train or refine models for specific experimental setups. It works across various cell types, fluorescent dyes, and microscopy techniques, including TIRF and confocal imaging.

The cells were imaged using a TIRF microscope with the 491 nm Cobolt 05-01 laser.

As they demonstrate, IVEA reduces analysis time by >90%, requiring minimal to no human input, and significantly decreases analysis bias. This innovation could accelerate research into diseases where exocytosis plays a critical role.