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Researchers created VirTues, a unified foundation model for spatial proteomics that translates diverse tissue imaging data into a standard language, enabling faster and more accurate medical diagnoses and personalized treatments.
A research paper integrates H&E-based deep learning recurrence risk heatmaps with mass spectrometry spatial proteomics to identify intratumoral molecular niches associated with recurrence in triple-negative breast cancer, achieving strong predictive performance and revealing distinct mitotic vs. immune programs.
SP-Mind is an autonomous AI agent that unifies spatial proteomics analysis pipelines, converting natural-language queries into end-to-end analytical workflows without fine-tuning, and achieves state-of-the-art performance on the new SP-Bench benchmark.