08/01/2026
🚨 𝗡𝗲𝘄 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝘁𝗼𝗼𝗹 𝗳𝗼𝗿 𝗰𝗹𝗮𝘀𝘀𝗶𝗳𝘆𝗶𝗻𝗴 𝗰𝗲𝗹𝗹 𝗱𝗲𝗮𝘁𝗵—𝗹𝗮𝗯𝗲𝗹-𝗳𝗿𝗲𝗲 & 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲!
We’re excited to share the very first 𝗵𝗼𝗹𝗼𝘁𝗼𝗺𝗼𝗴𝗿𝗮𝗽𝗵𝘆-𝗯𝗮𝘀𝗲𝗱 𝘀𝘁𝘂𝗱𝘆 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝗶𝗻 𝟮𝟬𝟮𝟲, showcasing the strength of our continued collaboration between Tomocube, Inc. and the 𝗞𝗔𝗜𝗦𝗧 𝗕𝗠𝗢𝗟 𝗟𝗮𝗯. Huge congratulations to the entire research team on this outstanding work! 🎉
Challenges in conventional cell death pathway classification methods:
❌ Fluorescence-based method: phototoxicity, bleaching, and limited duration for live-cell imaging.
❌ Existing label-free approaches: limited resolution and morphological insight, restricted classification (live or dead only), and lack of generalizability.
New study propose a 3D + deep learning framework that:
✅ Classifies apoptosis, necroptosis, necrosis, live-control, and drug-treated cells
✅ Achieves 97.2 ± 2.8% accuracy in HeLa cells
✅ Works in dense, unsegmented fields, up to 70% confluency
✅ Detects necroptotic changes 4–6 hrs earlier than FL markers (Annexin V/PI)
✅ Fully label-free, non-invasive, and scalable for high-throughput drug screening
A major step forward in dynamic, morphology-driven phenotyping. Read more: https://doi.org/10.1002/aisy.202500633
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