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Cell Death Discrimination with Raman Spectroscopy and Support Vector Machines

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Abstract

In the present study, Raman spectroscopy is employed to assess the potential toxicity of chemical substances. Having several advantages compared to other traditional methods, Raman spectroscopy is an ideal solution for investigating cells in their natural environment. In the present work, we combine the power of spectral resolution of Raman with one of the most widely used machine learning techniques. Support vector machines (SVMs) are used in the context of classification on a well established database. The database is constructed on three different classes: healthy cells, Triton X-100 (necrotic death), and etoposide (apoptotic death). SVM classifiers successfully assess the potential effect of the test toxins (Triton X-100, etoposide). The cells that are exposed to heat (45 °C) are tested using the classification rules obtained. It is shown that the heat effect results in apoptotic death, which is in agreement with existing literature.

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Acknowledgments

The authors are grateful for useful comments from two anonymous referees. The authors also acknowledge the financial support of the Particle Engineering Research Center (PERC) at the University of Florida, the State of Florida, the National Science Foundation (NSF Grant EEC-94-02989, NSF-NIRT Grant EEC-0506560, National High Field Magnet Laboratory), the National Institutes of Health (Grants 1-P20-RR020654-01, RO1HL75258, R01HL78670), and the Industrial Partners of the PERC for support of this research. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect those of the National Science Foundation. Research of Panos M. Pardalos is partially supported by NSF and Air Force grants.

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Authors and Affiliations

  1. Particle Engineering Research Center, University of Florida, Gainesville, FL, USA

    Georgios Pyrgiotakis, Kathryn Finton, Kevin Powers & Brij M. Moudgil

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    O. Erhun Kundakcioglu & Panos M. Pardalos

  3. Biochemistry Department, BMSD, University of Washington, Pullman, WA, USA

    Kathryn Finton

  4. Department of Materials Science and Engineering, University of Florida, Gainesville, FL, USA

    Brij M. Moudgil

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  1. Georgios Pyrgiotakis
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  2. O. Erhun Kundakcioglu
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  3. Kathryn Finton
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  4. Panos M. Pardalos
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  5. Kevin Powers
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  6. Brij M. Moudgil
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Correspondence to Panos M. Pardalos.

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Pyrgiotakis, G., Kundakcioglu, O.E., Finton, K. et al. Cell Death Discrimination with Raman Spectroscopy and Support Vector Machines. Ann Biomed Eng 37, 1464–1473 (2009). https://doi.org/10.1007/s10439-009-9688-z

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