The overall goal of the research program described in this grant application centers around the development of near infrared (NIR) spectroscopic chemical sensors for clinical and biomedical measurements. This novel sensing strategy offers the potential of continuously and noninvasively monitoring important clinical analytes in complex biological matrices. The proposed research is a collaboration between Professor Mark Arnold (University of Iowa), who will focus on the instrumental development aspects of the research, William Sivitz (Clinical Research Center, University of Iowa), who will focus on evaluation of the device on patients, and Professor Gary Small (Ohio University), who will focus on the data treatment. The emphasis of the research detailed in this proposal is the continued development of a noninvasive blood glucose sensor that can be used in the control and daily treatment of diabetes. Results are provided that illustrate the first demonstration of a valid blood glucose calibration model generated from noninvasive spectra. Experiments are proposed to improve the analytical performance of this system by enhancing both the quality of the NIR spectra and the data analysis algorithms used to extract the glucose information from the spectral information. A research strategy is proposed to establish the utility of both individual and global calibration models for in situ blood glucose levels. In addition, a series of novel NIR chemical sensors is proposed for continuously monitoring the process of hemodialysis. Sensing units are described for measuring urea accumulation in the dialysate fluid, urea and total protein in the newly dialyzed blood, and in situ levels of urea, total protein and albumin in the patient s body. This last group of sensors is based on noninvasive sensing strategies. These sensors will provide information that is not presently available to the practicing physician and this information can be used to: (1) establish and administer the ideal dialysis dose at every dialysis session; (2) improve patient nutrition; (3) avoid dialysis complications; and (4) prevent vascular access thrombosis. All of these features will have an instant impact on the morbidity and mortality of each patient undergoing dialysis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK045126-06
Application #
2734119
Study Section
Metallobiochemistry Study Section (BMT)
Program Officer
Harmon, Joan T
Project Start
1993-01-01
Project End
2000-06-30
Budget Start
1998-08-10
Budget End
1999-06-30
Support Year
6
Fiscal Year
1998
Total Cost
Indirect Cost
Name
University of Iowa
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
041294109
City
Iowa City
State
IA
Country
United States
Zip Code
52242
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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