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The blending of high-resolution imaging with machine learning is able to track cells that have been damaged from injury, aging, or disease, and no longer grow and reproduce normally, researchers say in a new study. Known to be integral to wound repair and aging-related diseases, such as cancer and heart disease, researchers say tracking the progress of senescent cells could give them an insight to understand more about how tissues slowly lose the capacity to regenerate over time or how they promote disease. The tool could also aid to understand therapies for reverting the damage.
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A Ground Breaking Discovery?
The study involved training computer systems with Artificial Intelligence to analyse animal cells that were injured by progressively increasing concentrations of chemicals over time to mimic human ageing. Cells that are persistently exposed to environmental or biological stressors, stop reproducing and begin to release matrix factors that provide an indication of an injury response. The study was published in the journal Nature on July 7, 2025. The team's AI analysis revealed several quantitatively measurable features of the cell's central control unit (nucleus) that when the features were considered collectively, correlated closely with the level of senescence in the tissue or group of cells. These features included evidence of nuclear enlargement, greater nuclear density (foci) and departure from a circular shape to an irregular shape. The genetic material within the nucleus stained more lightly than normal with standard chemical stains. Follow up quantifications established that cells with these features were senescent as they also showed signs of stopped reproduction, damaged DNA, packing of lysosomes that store enzymes in preparation for apoptosis, and responsiveness to existing senolytic medications.
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Potential To Improve Cancer Treatment?
"Our research provides evidence that certain nuclear morphometrics can be used to reliably identify and trace senescent cells, which we see as very important for future studies and understanding of tissue regeneration, aging, and progressive disease," said study's senior investigator Michael Wosczyna, PhD. Wosczyna is an assistant professor in the Department of Orthopedic Surgery, NYU Grossman School of Medicine. Wosczyna states that his team's NMP study validates accurate identification of senescent cells for any age and any tissue type, and across a range of diseases. The team plans further studies to explore the use of the NMP in human tissues, with hopes of combining the NMP with other types of biomarker tools to study senescence and the potential roles senescence may play in aging, wound repair, and disease. The researchers said the ultimate goal for the NMP, for which NYU has placed a patent application, is to develop therapies that prevent the negative effects of senescence on human health. "Our testing platform provides a robust platform to study senescent cells more readily than has been possible before, and to evaluate potential treatments, such as senolytics, that target senescent cells in different tissues and pathologies," Wosczyna added.
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Bottom Line
AI is the next big thing, if it is not already that. Despite all the reservations one might have against its (negative) potential, discoveries and advancements in medical science are undoubtedly one of its prudent attributes. It remains to be seen how AI and healthcare form a humane relationship going forward for the greater good.