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IR imaging-based AI offers a label-free and automated approach to identify lung tumor types

IR imaging-based AI offers a label-free and automated approach to identify lung tumor types Infrared spectroscopy can automatically distinguish between various types of lung cancer and genetic mutations, allowing quick and reliable statements to be made regarding prognosis and treatment decisions. The prognosis and effective therapies differ based on the type of lung cancer. While it previously took several days to precisely determine the underlying mutation, a research team at the Centre for Protein Diagnostics (PRODI) at Ruhr-Universität Bochum (RUB) has been able to reliably perform this determination in just one step using a combination of quantum cascade laser-based infrared microscopy and artificial intelligence. The examined tissue does not need to be marked for this. The analysis only takes around half an hour. “This is a major step that shows that infrared imaging can be a promising methodology in future diagnostic testing and treatment prediction,” says Professor Kla

Label-Free Digital Pathology Helps Detect Lung Cancer

Label-Free Digital Pathology Helps Detect Lung Cancer
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Researchers gain new insights into the structure of cancer-promoting Ras protein

Cancer-promoting Ras protein exists in a pair within cells

Credit: PRODI/ Till Rudack Researchers from Bochum and Osnabrück have gained new insights into the structure of the Ras protein, which acts as a molecular switch for cell growth and is involved in the development of cancer. With the help of fluorescence markings, they have demonstrated that the protein is deposited in a pair at the cell membrane, and with the very structure that they predicted in theory back in 2012. The team from the Bochum Center for Protein Diagnostics (PRODI) hopes that these findings will open up a new approach for the development of cancer medications. The researchers from Ruhr-Universität Bochum (RUB) and Osnabrück University published the results in the

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