We are pleased to share that our partners at Preste have published the new paper "Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning" in Wiley Advanced Intelligence discovery, presenting a machine learning-based methodology for classifying macrophage phenotypes.

This innovative approach uses only fluorescence intensity data, eliminating the need for conventional cellular markers. It represents a significant step forward in analyzing and understanding macrophage-biomaterial interactions, especially in the context of biomedical applications and disease modeling.

The study was led by Oleh Mezhenskyi, Tetiana Goldanova, and Kateryna Andriienkova, and reflects Preste’s ongoing contribution to the NOVA Project.

Read the full open-access article.

We congratulate the Preste team on this achievement and look forward to further joint discoveries within the NOVA collaboration.