| Mar 10, 2025 |
A novel nanotechnology approach identifies subtle cellular differences, enhancing early disease diagnosis and potentially improving outcomes for chronic conditions and cancer.
(Nanowerk News) Early diagnosis is crucial in disease prevention and treatment. Many diseases can be identified not just through physical signs and symptoms but also through changes at the cellular and molecular levels.
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When it comes to a majority of chronic conditions early detection, particularly at the cellular level, gives patients a better chance for successful treatment. Detection of early changes at the cellular level can also dramatically improve cancer outcomes.
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It’s against this backdrop that a University of Rhode Island professor, and a former PhD graduate student looked at understanding the smallest changes between two similar cells.
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Daniel Roxbury, an associate professor of chemical engineering at the University of Rhode Island, and recently graduated doctoral researcher Acer Nadeem recently published a proof-of-concept paper in ACS Nano (“Machine Learning-Assisted Near-Infrared Spectral Fingerprinting for Macrophage Phenotyping”) demonstrating how the use of carbon nanotubes could be combined with machine learning to detect subtle differences between closely related immune cells. The cells they worked with were macrophages of the M1 and M2 variety, that help fight infection as well as sterilize and heal wounds. Expanding on this research could eventually aid in the early detection of diseases like cancer.
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Carbon nanotubes are aptly named. They’re composed of a single sheet of carbon atoms and are so small that thousands of them can fit inside a living cell. A unique thing about them are their fluorescent properties, which allow them to emit a distinct optical signature when exposed to infrared light.
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“When added to cells, we can use the light given off by nanotubes to detect minute differences between closely related cells,” said Roxbury.
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These nanotubes emit a variety of infrared light. Broadly speaking, by looking at variations in the infrared light emitted from the nanotubes, they can detect diverse cellular changes, including pH levels, protein concentrations, and ion variations. This can be particularly important because research shows that high pH levels are linked to an increased likelihood of a tumor.
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Nanotubes are commonly used in applications like composite materials and carbon fiber, but Roxbury and Nadeem are using them in a novel way at URI – to distinguish between healthy and unhealthy cells.
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Nadeem was tasked with developing new sensors using carbon nanotubes to detect proteins in the blood that would help identify cancer.
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“Inside the cell are a million different proteins, lipids, and sugars,” said Nadeem. “So, starting this project, we didn’t know if we were actually going to see anything reflected back from the nanotubes because all these different proteins andions aren’t in a very high concentration inside a cell.”
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For Nadeem, it was a welcomed challenge. Researching and studying methods to detect some of the most common diseases early on was critical for him. Part of Nadeem’s motivation was the fact that he has a family history of Alzheimer’s disease and was eager to develop better methods for early detection.
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“I wanted to figure out a way to diagnose these diseases—neurodegenerative diseases as well as cancer—in their very early stages,” said Nadeem.
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Roxbury and Nadeem used an in vitro experiment that involved placing live cells into a culture dish, adding carbon nanotubes, and then using a specialized microscope with an infrared camera to observe the emitted light from each cell.
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The camera generated millions of data points. Each data point reflected cellular activity. Healthy cells emitted one type of light, while potentially unhealthy or changing cells emitted different light patterns.
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“Analyzing the data was what took the most time,” said Nadeem. “That’s where integrating machine learning came into this project because we got around four million-plus data points.”
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Integrating machine learning allowed the researchers to distill those millions of data points into a comprehensive understanding of what was happening at the cellular level, such as high or low acidity.
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“As a direct continuation of Aceer’s work, we are currently working to discern cancer versus non-cancer,” said Roxbury. “We’ve demonstrated immune cell discrimination. We are now looking at breast cancer cells and tissue versus healthy breast tissue and trying to uncover the difference there.”
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While it will be some time before experiments will be able to be translated to animals, the potential industry uses are vast. Nanotubes could potentially be used inside the human body to help in the early detection of not only cancer, but Alzheimer’s and other diseases, making it less expensive and leading to a quicker diagnosis.
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“All of these different diseases have their own distinct biomarkers with them, even at the very early stage,” said Nadeem. “So, there is immense potential to use this as an early diagnostic tool for many diseases.”
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