AI-powered microscopy to combat infections

Ricardo Henriques

Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Portugal

Current high-resolution microscopes damage living cells with intense light, limiting the ability to observe complete viral infection cycles. This fundamental problem has left significant gaps in the understanding of how viruses like HIV-1 enter cells, establish latency, and interact with host cells. This project aims to address this challenge by using artificial intelligence to adjust the microscope's settings in real-time, similar to how modern phones optimize photo settings but at a more sophisticated level.

By combining multiple advanced imaging techniques with smart algorithms, this technology will allow scientists to observe viral infections for days rather than minutes, while maintaining exceptional detail. This breakthrough will enable researchers to track sub-cellular infection processes, revealing crucial details about viral entry, latency, and spread.

In conclusion, this project represents a significant leap forward in microscopy technology, offering a powerful new tool for understanding and combating viral infections. By making advanced imaging accessible to a wide range of research environments, this project will democratize scientific discovery and improve public health outcomes worldwide.

VirusAwareScopes: Machine Learning-Driven Adaptive Microscopy for Long-Term Viral Infection Studies

€499.833,52