The overall goal of this research program is to develop spectroscopic- based glucose sensors that can be used in the treatment and control of diabetes. this sensing approach will be based on near-infrared (NIR) spectroscopy, state-of-the-art optical fiber technology, and advanced computer-based data analysis. The focus of the proposed work is the design, construction, and evaluation of a noninvasive sensor that will allow direct measurement of in situ blood glucose levels without collecting a blood sample. The proposed research is built upon a series of experiments designed to show conclusively that NIR spectroscopy, coupled with computer-based data analysis, can be used to determine glucose quantitatively in the 1 - 20 mM concentration range in biological matrices. The work described in this grant application consists of four major components: (1) extension of our initial feasibility studies to increase the complexity of the sample matrix; (2) investigation of the impact of instrumental parameters on the proposed analysis; (3) development of optimized data analysis algorithms for extracting glucose information from the collected NIR spectra; and (4) development of glucose sensing probes based on optical fiber technology. Throughout the proposed work, the principal focus of our research efforts will be to develop precise and accurate glucose sensing methods that are amenable to practical implementation.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
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Metallobiochemistry Study Section (BMT)
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University of Iowa
Schools of Arts and Sciences
Iowa City
United States
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Olesberg, Jonathon T; Arnold, Mark A; Flanigan, Michael J (2004) Online measurement of urea concentration in spent dialysate during hemodialysis. Clin Chem 50:175-81
Eddy, Christopher V; Flanigan, Michael; Arnold, Mark A (2003) Near-infrared spectroscopic measurement of urea in dialysate samples collected during hemodialysis treatments. Appl Spectrosc 57:1230-5
Zhang, Lin; Small, Gary W; Arnold, Mark A (2002) Calibration standardization algorithm for partial least-squares regression: application to the determination of physiological levels of glucose by near-infrared spectroscopy. Anal Chem 74:4097-108
Eddy, C V; Arnold, M A (2001) Near-infrared spectroscopy for measuring urea in hemodialysis fluids. Clin Chem 47:1279-86
Burmeister, J J; Arnold, M A; Small, G W (2000) Noninvasive blood glucose measurements by near-infrared transmission spectroscopy across human tongues. Diabetes Technol Ther 2:16-May
Burmeister, J J; Chung, H; Arnold, M A (1998) Phantoms for noninvasive blood glucose sensing with near infrared transmission spectroscopy. Photochem Photobiol 67:50-5
Arnold, M A; Burmeister, J J; Small, G W (1998) Phantom glucose calibration models from simulated noninvasive human near-infrared spectra. Anal Chem 70:1773-81
Ding, Q; Small, G W; Arnold, M A (1998) Genetic algorithm-based wavelength selection for the near-infrared determination of glucose in biological matrixes: initialization strategies and effects of spectral resolution. Anal Chem 70:4472-9
Mattu, M J; Small, G W; Arnold, M A (1997) Determination of glucose in a biological matrix by multivariate analysis of multiple band-pass-filtered Fourier transform near-infrared interferograms. Anal Chem 69:4695-702
Shaffer, R E; Small, G W; Arnold, M A (1996) Genetic algorithm-based protocol for coupling digital filtering and partial least-squares regression: application to the near-infrared analysis of glucose in biological matrices. Anal Chem 68:2663-75

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