B.S., Indiana University-Purdue University at Indianapolis (1978) Ph.D., University of Delaware (1982)

Analytical Chemistry

Additional link: Optical Science and Technology Center Chemical sensing technology is being developed for applications in biomedical research, clinical chemistry, neuroscience, bioprocess monitoring, biotechnology, and environmental sciences. Spectroscopic and optical methods are used to measure selected chemical analytes in complex matrices. Examples include noninvasive blood glucose sensing in people with diabetes , on-line systemic urea monitoring during hemodialysis treatments, real-time monitoring of cellular nutrients and metabolites in functioning bioreactors, and remote, continuous dissolved oxygen measurements in biological systems. Near infrared spectroscopy is being developed to measure blood glucose levels in human subjects both painlessly and noninvasively. The concept is to pass a harmless band of near infrared light through the human body and then extract the glucose concentration information from the transmitted spectral radiation. Digital filtering techniques and multivariate calibration methods, such as partial least-squares regression, are used to extract glucose information accurately from noninvasive near infrared spectra collected from complex biological matrices. We have developed an in vitro model of the human body to help identify and characterize experimental parameters that are critical for noninvasive blood glucose measurements. Investigated parameters include scattering, spectrometer signal-to-noise ratios, optical path length and spectral correlations within a data set. Complications of spectral correlations can be considerable when sample glucose levels correlate with other chemical species within the sample matrix. More importantly, temporal correlations can greatly impact analytical performance. Experimental design methods must be applied to avoid bogus calibration models created by such correlations. In addition to blood glucose, we are presently exploring the application of near infrared spectroscopy for measuring: systemic urea during hemodialysis treatments, glucose, lactate, ammonia, and glutamine during cultivation of mammalian and insect cells, dissolved protein during crystallization, and methanol levels used to induce microbial recombinant processes. Many sensor applications demand continuous operation over extended periods without user intervention. The measurement of dissolved oxygen in growth media during bioreactor operation on-board the Space Shuttle is one such application. Sensor recalibration is not possible after the shuttle is launched, which means measurement accuracy requires stable calibrations. Stable chemical sensors are being developed for remote sensing by using radioluminescent (RL) light sources. Our RL sources are composed of tritium gas coupled with an inorganic phosphor. Beta emission from the tritium excites a phosphor and the excited phosphor subsequently relaxes to produces a photon. RL-optical sensors for dissolved oxygen are being developed on the basis of dynamic fluorescence quenching of immobilized ruthenium complexes. Low noise and high stability of RL sources provide low detection limits and long term stability. Kromoscopy is a new measurement code for analytical science. In this method, white light passes through the sample and the transmitted light is divided into four separate detector channels. The response function of each channel is defined by the source, detector, and bandpass function of a filter that is position immediately before the detector. Each chemical species displays a unique Kromoscopic response when represented as a vector in the multidimensional space defined by the four detector signals. Tremendously high signal-to-noise ratios are possible with this instrument configuration. We are presently characterizing the selectivity of Kromoscopy by defining conditions under which glucose can be measured at clinically relevant concentrations in the presence of common, endogenous interferences, such as urea, triglycerides, hemoglobin, cholesterol, and protein.

Nankung, H; Kim, J; Chung, H; Arnold, MA; Impact of pellet thickness on quantitative terahertz spectroscopy of solid samples in a polyethylene matrix; 2012, submitted for publication Xiang, D; Arnold, MA; Chemical imaging with a solid-state near infrared spectrometer based on a digital micro-mirror array device coupled with Hadamard transform spectroscopy; Analytical Letters 2012, 45:9, 1070-1078 Smith, RM; Arnold, MA; Terahertz time-domain spectroscopy of solid samples: Principles, applications, and challenges; Applied Spectroscopy Review 2011, 46 636-679. Xiang, D; Arnold, MA; Solid-state digital micro-mirror array near infrared spectrometer for Hadamard transform analytical spectroscopy; Applied Spectroscopy, 2011 65 1170-1180. Sacks DB; Arnold, M; Bakris, GL; Bruns, DE; Horvath, AR; Kirkman, MS; Lernmark, A; Metzger, BE; Nathan, DM; Executive Summary: Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus; Clinical Chemistry 2011, 57 793-798. Sacks DB; Arnold, M; Bakris, GL; Bruns, DE; Horvath, AR; Kirkman, MS; Lernmark, A; Metzger, BE; Nathan, DM; Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus; Clinical Chemistry 2011, 57 e1-e47. Park, SC; Shinzawa, H; Chung, H; Ozaki, Y; Arnold, MA; Improved Accuracy for Raman Spectroscopic Determination of Polyethylene Property by Optimization of Measurement Temperature and Elucidation of Its Origin by Multiple Perturbation Two-Dimensional Correlation Spectroscopy; Analyst 2011 136, 3121-3129. Alexeeva, NV; Arnold, MA; Impact of tissue heterogeneity on noninvasive near infrared glucose measurements in interstitial fluid of rat skin; Journal of Diabetes Science and Technology 2010; 4:1041-1054. Tarumi, T; Amerov, AK; Arnold, MA; Small, GW; Design considerations for near-infrared filter photometry: effects of noise sources and selectivity; Applied Spectroscopy 2009 63:700-708 Alexeeva, NV; Arnold, MA; Near infrared micro-spectroscopic analysis of rat skin tissue heterogeneity in relation to noninvasive glucose sensing; Journal of Diabetes Science and Technology 2009 3, 219-232 Arnold, MA; Olesberg, JT; Small, GW; Near-infrared spectroscopy for noninvasive glucose sensing; in Analytical Chemistry of In Vivo Glucose Measurements; Cunningham, D.; Stenken, JA, Eds.; Wiley Chemical Analysis Series, 2009, Chapter 13 Shih, W-C; Bechtel, KL; Feld, MS; Arnold, MA; Small, GW; Introduction to spectroscopy for noninvasive glucose sensing; in Analytical Chemistry of In Vivo Glucose Measurements; Cunningham, D.; Stenken, JA, Eds.; Wiley Chemical Analysis Series, 2009, Chapter 12. Liu, L; Arnold, MA: Selectivity for glucose, glucose-6-phosphate, and pyruvate in ternary mixtures from the multivariate analysis of near infrared spectra; Analytical and Bioanalytical Chemistry 2009, 393, 669-677. Bai, C.; Graham, TL; Arnold, MA; Assessing and advancing technology for the noninvasive measurement of clinical glucose; Analytical Letters 2008, 41, 2773-2793. acks, DB; Arnold, MA: Diabetic control with non-invasive devices; Proceedings XVI Winter Course: Quality Control in Telemedicine.Biobanking (Ed. Ferrer-Roca O) 2008, 81-85. Cho, DS; Olesberg, JT; Flanigan, MJ; Arnold, MA: On Line near infrared spectrometer to monitor urea removal in real-time during hemodialysis; Applied Spectroscopy , 2008 62,866-872 Arnold, MA; Liu, L; Olesberg, JT: Selectivity assessment of noninvasive glucose measurements based on analysis of multivariate calibration vectors; Journal of Diabetes Science and Technology, 2007 1(4) , 454-462. Reece, JA; Murhammer, DW; Arnold, MA; Radioluminescent oxygen sensor for monitoring dynamic oxygen concentrations during cell cultivation; submitted for publication Ren, M; Arnold, MA; Comparison of multivariate calibration models for glucose, lactate and urea from near infrared and Raman spectra; Analytical and Bioanalytical Chemistry 2007 387, 879-888. Lee, Y-B; Chung, H; Arnold, MA; Improving the robustness of a PLS model based on pure component selectivity analysis and range optimization: Case study for the analysis of an etching solution containing hydrogen peroxide; Analytica Chimica Acta 2006 572, 93-101.