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Reagentless Determination of Human Serum Components Using Infrared Absorption Spectroscopy

  • Hahn, Sang-Joon (u-Health Project Team, Samsung Advanced Institute of Technology) ;
  • Yoon, Gil-Won (Seoul National University of Technology) ;
  • Kim Gun-Shik (National Research Laboratory of Nonlinear Optics, College of Science, Yonsei University) ;
  • Park Seung-Han (National Research Laboratory of Nonlinear Optics, College of Science, Yonsei University)
  • Received : 2003.10.07
  • Published : 2003.12.01

Abstract

Simultaneous determination of concentrations for four major components in human blood serum was investigated using a Fourier-transform mid-infrared spectroscopy. Infrared spectra of human blood serum were measured in 8.404 ∼ 10.25 ${\mu}m$ range where the highest absorption peaks of glucose are located. A partial least square (PLS) algorithm was utilized to establish a calibration model for determining total protein, albumin, globulin and glucose levels which are commonly measured metabolites. The standard error of cross validation obtained from our multivariate calibration model was 0.24 g/dL for total protein, 0.15 g/dL for albumin, 0.17 g/dL for globulin, and 6.68 mg/dL for glucose, which are comparable with or meet the criteria for clinical use. The results indicate that the infrared absorption spectroscopy can be used to predict the concentrations of clinically important metabolites without going through a chemical process with a reagent.

Keywords

References

  1. G. Budinova, J. Salva, and K. Volka, 'Application of Molecular Spectroscopy in the Mid-Infrared Region to the Determination of Glucose and Cholesterol in Whole Blood and in Blood Serum,' Appl. Spectrosc., vol. 51, no. 5, pp. 631-639, 1997 https://doi.org/10.1366/0003702971941034
  2. G. Janatsch, and J. D. Kruse-Jarres, 'Multivariate calibration for assays in clinical chemistry using attenuated total reflection infrared spectra of human blood plasma,' Anal. Chem., vol. 61, p. 2016, 1989 https://doi.org/10.1021/ac00193a005
  3. F. Cadet, C. Robert, and B. Offmann, 'Simultaneous Determination of Sugars by Multivariate Analysis Applied to Mid-Infrared Spectra of Biological Samples,' Appl. Spectrosc., vol. 51, no. 3, pp. 369-375, 1997 https://doi.org/10.1366/0003702971940224
  4. R Vonach, J. Buschmann, R. Falkowski, R. Schindler, B. Lendl, and R. Kellner, 'Application of MidInfrared Transmission Spectrometry to the Direct Determination of Glucose in Whole Blood,' Appl. Specirosc., vol. 51, no. 6, pp. 820-822, 1998 https://doi.org/10.1366/0003702981944553
  5. H. M. Heise and R.Marbach, 'Human oral mucosa studies with varying blood glucose concentration by non-invasive ATR-FT-IR-Spectroscopy,' Cellular and Molecular Biology, vol. 44, no. 6, pp. 899-912, 1998
  6. N. A. Cingo, G. W. Small, and M. A. Arnold, 'Determination of glucose in a synthetic biological matrix with decimated time-domain filtered near-infrared interferogram data,' Vib. Spec., vol. 23, pp. 103-117, 2000 https://doi.org/10.1016/S0924-2031(99)00089-2
  7. I. Amato, 'In Search of Human Touch,' Science, vol. 258, no. 5085, pp. 892-895, 1992 https://doi.org/10.1126/science.1439836
  8. M. A. Arnold, G. W. Small, 'Determination of physiological levels of glucose in an aqueous matrix with digitally filtered Fourier transform near-infrared spectra,' Anal. Chem., vol. 62, no. 14, pp. 1457-1464 (1990) https://doi.org/10.1021/ac00213a021
  9. R. A. Shaw and H. H. Mantsch, 'Multianalyte Serum Assays from Mid-IR Spectra of Dry Films on Glass Slides,' Appl. Specirosc., vol. 54, no. 6, pp. 885-889, 2000 https://doi.org/10.1366/0003702001950265
  10. H. Martens and T. Naes, Multivariate Calibration (John Wiley and Sons, New York, 1989), pp. 1-30
  11. R. Kramer, Chemometric Techniques for Quantitative Analysis (Marcel Dekker, Inc., New York, 1998) pp.1-8
  12. H. M. Heise, Infrared and Raman Spectroscopy of Biological Materials, U-H Gremlich and B. Yan Eds., (Marcel Dekker, New York, 2001), pp. 259-322
  13. O. S. Khalil, 'Spectroscopic and Clinical Aspects of Noninvasive Glucose Measurements,' Clin. Chem., vol. 45, no. 2, pp. 165-177, 1999
  14. S. Sasic and Y. Ozaki, 'Statistical Two-Dimensional Correlation Spectroscopy: Its Theory and Applications to Sets of Vibrational Spectra,' Anal. Chem., vol. 73, no. 10, pp. 2294-2301, 2001 https://doi.org/10.1021/ac0014010
  15. C. A. Burtis and E. R. Ashwood, Tietz Textbook of Clinical Chemistry (3rd edition, W.B. Saunders Co., 1999) pp. 375-377

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