Biomedical subjects

M A Arnold

Publications and source records attributed to M A Arnold.

At least 19 recordsLinked to original sources

PubMed1999

Mercury distribution in blood, tissues, and feathers of double-crested cormorant nestlings from arid-lands reservoirs in south central New Mexico.

Eggs, blood, liver, muscle, and feathers were analyzed for concentrations of total mercury in double-crested cormorant (Phalacrocorax auritus) nestlings from two reservoirs in south central New Mexico. Total mercury concentrations among eggs, tissues, and feathers were not significantly correlated. Concentrations of total mercury averaged 0.40 microg/g in liver and 0.18 microg/g in muscle tissues in both populations of nestlings. There were no significant changes in concentrations of total mercury in whole blood of nestlings collected 7-10 days and 17-22 days posthatch in Caballo Reservoir (0.36 microg/g and 0.39 microg/g, respectively) and in Elephant Butte Reservoir (0.36 microg/g and 0.34 microg/g, respectively). Total mercury concentrations were similar for blood, muscle, and liver in nestlings for both reservoirs. Total mercury concentrations were higher in eggs and tail, primary, and secondary feathers from nestlings at Caballo Reservoir compared to Elephant Butte Reservoir. Although there were no differences in concentrations of total mercury in fishes between the two reservoirs, bioaccumulation and biomagnification was evident in planktivorous and piscivorous fishes. The data demonstrate that feather analysis may not be a good predictor of tissue burden in nestlings from regions of low contamination.

Animals↗

PubMed1998

Genetic algorithm-based wavelength selection for the near-infrared determination of glucose in biological matrixes: initialization strategies and effects of spectral resolution.

An improved genetic algorithm (GA)-based wavelength selection procedure is developed to optimize both the near-infrared wavelengths used and the number of latent variables employed in building partial least-squares (PLS) calibration models. This GA-based wavelength selection algorithm is applied to the determination of glucose in two different biological matrixes. With random selection of a small number of initial wavelengths, a dramatic reduction in the number of wavelengths required for building the PLS calibration models is observed. The fitness function used to guide the GA, the method of recombination used, and the effect of spectral resolution on the wavelength selection are also studied. In the resolution study, the original data with a point spacing of 2 cm-1 are deresolved to 4-, 8-, and 16-cm-1 point spacings by truncating the collected interferograms before applying the Fourier processing step. The use of lower resolution spectra is found to reduce further the number of final wavelengths selected by the GA, and the performance of the optimal calibration models obtained with the original spectra is maintained with the lower resolution spectra of both 4- and 8-cm-1 point spacing. Degradation in performance is observed with the spectra computed with a point spacing of 16 cm-1, however.

Algorithms↗

PubMed1998

Phantom glucose calibration models from simulated noninvasive human near-infrared spectra.

The validity of published reports claiming to have successfully measured in vivo blood glucose from noninvasive near-infrared spectra collected in a time-dependent manner is challenged on the basis of results obtained from a phantom glucose spectral data set. An in vitro model is used to simulate noninvasive human near-IR spectra. The phantom glucose data set is created by purposely omitting glucose in these modeled samples. Glucose values are then assigned to successive phantom glucose spectra, and multivariate calibration models are generated for glucose based on partial-least squares regression. As expected, calibration models are incapable of predicting glucose values when the glucose assignments are made randomly. Apparently functional models are obtained, however, when glucose assignments are made in a nonrandom, time-dependent manner. Prediction errors from these nonrandom models are essentially identical to those published by other as evidence of successful noninvasive blood glucose measurements. Chance temporal correlations between assigned glucose concentrations and some uncontrolled experimental parameter are responsible for this apparent model functionality.

Calibration↗

PubMed1998

Phantoms for noninvasive blood glucose sensing with near infrared transmission spectroscopy.

In vivo spectra from human subjects can be simulated with a phantom composed of different layers of water, fat and muscle tissue. All three components are necessary to simulate in vivo spectra collected over the combination spectral region (5000-4000 cm-1). Muscle tissue is not required, however, to accurately simulate overtone spectra (6600-5400 cm-1). The near-IR spectral characteristics of fat and muscle tissue from several animal sources are essentially identical to those found for human tissue, hence, the animal source for these phantom components is not critical. Thickness of each tissue layer can be determined by a regression analysis where the in vivo spectrum of interest is regressed against standard absorbance spectra of the necessary model components (water, fat and muscle). In general, in vivo overtone spectra collected across human webbing tissue with a thickness of 6.7 mm can be simulated with water layer thicknesses ranging from 5.0 to 6.4 mm combined with fat layer thicknesses from 1.4 to 4.2 mm.

Animals↗

PubMed1998

4-tert-butylperoxymethyl-9-methoxypsoralen as intercalating photochemical alkoxyl-radical source for oxidative DNA damage.

We describe the synthesis of a novel psoralen peroxide 1 that generates on irradiation (350 nm) alkoxyl radicals, namely tert-butoxyl radicals, as confirmed by electron spin resonance studies with the spin trap 5,5-dimethyl-pyrroline-N-oxide. The radical source intercalates into the DNA, which has been demonstrated by linear-flow-dichroism measurements. Thus, the alkoxyl radicals are formed advantageously directly in the DNA matrix. In supercoiled pBR322 DNA, the generation of strand breaks by the photochemically or metal-catalyzed generated alkoxyl radicals is demonstrated. Photosensitization by the psoralen chromophore was excluded because similar substances that do not release radicals caused no DNA damage, nor were the photoproducts of the peroxide 1 active. With calf thymus DNA, 8-oxoGua and small amounts of guanidine-releasing products, e.g. oxazolone, were observed. However, in these reactions the photoproduct also displayed some DNA-oxidizing capacity.

Cyclic N-Oxides↗

PubMed1997

Determination of glucose in a biological matrix by multivariate analysis of multiple band-pass-filtered Fourier transform near-infrared interferograms.

A multivariate calibration method is described in which Fourier transform near-infrared interferogram data are used to determine clinically relevant levels of glucose in an aqueous matrix of bovine serum albumin (BSA) and triacetin. BSA and triacetin are used to model the protein and triglycerides in blood, respectively, and are present in levels spanning the normal human physiological range. A full factorial experimental design is constructed for the data collection, with glucose at 10 levels, BSA at 4 levels, and triacetin at 4 levels. Gaussian-shaped band-pass digital filters are applied to the interferogram data to extract frequencies associated with an absorption band of interest. Separate filters of various widths are positioned on the glucose band at 4400 cm-1, the BSA band at 4606 cm-1, and the triacetin band at 4446 cm-1. Each filter is applied to the raw interferogram, producing one, two, or three filtered interferograms, depending on the number of filters used. Segments of these filtered interferograms are used together in a partial least-squares regression analysis to build glucose calibration models. The optimal calibration model is realized by use of separate segments of interferograms filtered with three filters centered on the glucose, BSA, and triacetin bands. Over the physiological range of 1-20 mM glucose, this 17-term model exhibits values of R2, standard error of calibration, and standard error of prediction of 98.85%, 0.631 mM, and 0.677 mM, respectively. These results are comparable to those obtained in a conventional analysis of spectral data. The interferogram-based method operates without the use of a separate background measurement and employs only a short section of the interferogram.

Animals↗

PubMed1996

Genetic algorithm-based method for selecting wavelengths and model size for use with partial least-squares regression: application to near-infrared spectroscopy.

Genetic algorithms (GAs) are used to implement an automated wavelength selection procedure for use in building multivariate calibration models based on partial least-squares regression. The method also allows the number of latent variables used in constructing the calibration models to be optimized along with the selection of the wavelengths. The data used to test this methodology are derived from the determination of aqueous organic species by near-infrared spectroscopy. The three data sets employed focus on the determination of (1) methyl isobutyl ketone in water over the range of 1-160 ppm, (2) physiological levels of glucose in a phosphate buffer matrix containing bovine serum albumin and triacetin, and (3) glucose in a human serum matrix. These data sets feature analyte signals near the limit of detection and the presence of significant spectral interferences. Studies are performed to characterize the signal and noise characteristics of the spectral data, and optimal configurations for the GA are found for each data set through experimental design techniques. Despite the complexity of the spectral data, the GA procedure is found to perform well, leading to calibration models that significantly outperform those based on full spectrum analyses. In addition, a significant reduction in the number of spectral points required to build the models is realized.

Algorithms↗

PubMed1996

Genetic algorithm-based protocol for coupling digital filtering and partial least-squares regression: application to the near-infrared analysis of glucose in biological matrices.

A multivariate calibration procedure is described that is based on the use of a genetic algorithm (GA) to guide the coupling of bandpass digital filtering and partial least-squares (PLS) regression. The measurement of glucose in three different biological matrices with near-infrared spectroscopy is employed to develop this protocol. The GA is employed to optimize the position and width of the bandpass digital filter, the spectral range for PLS regression, and the number of PLS factors used in building the calibration model. The optimization of these variables is difficult because the values of the variables employ different units, resulting in a tendency for local optima to occur on the response surface of the optimization. Two issues are found to be critical to the success of the optimization: the configuration of the GA and the development of an appropriate fitness function. An integer representation for the GA is employed to overcome the difficulty in optimizing variables that are dissimilar, and the optimal GA configuration is found through experimental design methods. Three fitness function calculations are compared for their ability to lead the GA to better calibration models. A fitness function based on the combination of the mean-squared error in the calibration set data, the mean-squared error in the monitoring set data, and the number of PLS factors raised to a weighting factor is found to perform best. Multiple random drawings of the calibration and monitoring sets are also found to improve the optimization performance. Using this fitness function and three random drawings of the calibration and monitoring sets, the GA found calibration models that required fewer PLS factors yet had similar or better prediction abilities compared to calibration models found through an optimization protocol based on a grid search method.

Algorithms↗

PubMed1996

Near-infrared spectroscopic measurement of physiological glucose levels in variable matrices of protein and triglycerides.

Selective calibration models are generated for glucose over the 1-20 nM concentration range by use of partial least-squares regression analysis of near-infrared spectra from 5000 to 4000 cm-1. Two spectral data sets are used to simulate triglyceride and protein variations in clinical samples. Triacetin is used in one data set to simulate variations in triglyceride levels, and bovine serum albumin (BSA) is used in the second data set to simulate variations in blood protein levels. Although these matrix components possess strong absorption bands that overlap and overshadow the absorption bands of glucose, successful calibration models can be generated with no evidence of prediction bias caused by the different levels of the matrix components. Furthermore, the benefits of using digital Fourier filtering as a preprocessing step are evaluated in terms of calibration performance. The resulting calibration models provide standard errors of prediction of 0.5 and 0.2 mM in triacetin and BSA matrices, respectively. Accurate glucose predictions are demonstrated from spectra that correspond to protein concentrations not present in the calibration data set. Lastly, digital Fourier filtering alone is shown to have only limited ability to isolate glucose signals from those of BSA and triacetin due to similarities in the widths of the absorption bands of the three species.

Animals↗

PubMed1996

Optical detection of hemoglobin in pulpal blood.

An in vitro, flow-through optical system was designed to measure hemoglobin (Hb) concentrations in the pulp space. The system included light-emitting diodes and a silicon photodetector positioned on opposing surfaces of human teeth. A syringe pump allowed a controlled flow of blood through the pulp chamber. The Hb concentration was computed as a nonlinear function of transmitted light intensity. Transmitted light intensities were also used as indicators of oxygenation level. Optical measurements correlated with Hb values measured by the conventional cyanmethemoglobin method (r=0.993). The mean percentage error was 5.8%, and the standard error of prediction was 0.77 g/dl for Hb concentrations ranging from 4 to 20 g/dl. Deoxygenated blood exhibited up to 31% lower transmitted intensity. Light transmission through teeth may be useful in the assessment of total Hb and blood oxygenation within the pulp chamber.

Animals↗

PubMed1996

Non-invasive glucose monitoring.

Several recent reports claim success in measuring blood glucose non-invasively in human subjects with near-infrared spectroscopy. A critical examination of these published results suggests more fundamental research is needed to verify the validity of these claims. In addition, progress continues in assessing the utility of near-infrared spectroscopy as a non-invasive probe for continuous bioreactor monitoring during fermentation processes. Recent work demonstrates that five critical fermentation components, including glucose, may be measured simultaneously.

Biosensing Techniques↗

PubMed1995

Simultaneous measurement of glucose and glutamine in aqueous solutions by near infrared spectroscopy.

A method is described for measuring the concentrations of both glucose and glutamine in binary mixtures from near infrared (NIR) absorption spectra. Spectra are collected over the range from 5000-4000/cm (2.0-2.5 microns) with a 1-mm optical path length. Glucose absorbance features at 4710, 4400, and 4300/cm and glutamine features at 4700, 4580, and 4390/cm provide the analytical information required for the measurement. Multivariate calibration models are generated by using partial least squares (PLS) regression alone and PLS regression combined with a preprocessing digital Fourier filtering step. The ideal number of PLS factors and spectral range are identified separately for each analyte. In addition, the optimum Fourier filter parameters are established for both compounds. The best overall analytical performance is obtained by combining Fourier filtering and PLS regression. Glucose measurements are established over the concentration range from 1.66-59.91 mM, with a standard error of prediction (SEP) of 0.32 mM and a mean percent error of 1.84%. Glutamine can be measured over the concentration range from 1.10-30.65 mM with a SEP of 0.75 mM and a mean percent error of 6.67%. These results demonstrate the analytical utility of NIR spectroscopy for monitoring glucose and glutamine levels in mammalian and insect cell cultures.

Buffers↗

PubMed1994

Optical detection of pulpal blood.

An optical system to assess blood within the pulpal cavity was developed. The system included a light-emitting diode source, human incisor teeth, and a silicon photodiode detector. An automated syringe pump was used to flow bovine blood lengthwise through the teeth. Transmitted light intensities were recorded at a collection frequency of 20 reading/min and apparent absorbance units were calculated. The effects of blood concentration, blood flow rate, and pulp chamber size were investigated. It was found that changes in blood flow rate did not cause significant changes in transmitted light intensity. Increases in blood concentration and pulp chamber size resulted in larger absorbance values. These results suggest that photoplethysmography measurements may be sensitive to the amount of blood in the pulp chamber as it reflects the pulsatile-related expansion and contraction of capillaries within the pulp tissue.

Animals↗

PubMed1993

Near-infrared spectroscopic measurement of glucose in a protein matrix.

A method is described for measuring clinically relevant levels of glucose in a protein matrix by near-infrared (near-IR) absorption spectroscopy. Results from an initial screening of major blood constituents identify protein as a major potential interference to the near-IR measurement of glucose in blood. The interference by protein is caused by relatively high concentrations coupled with strong near-IR absorption bands between 5000 and 4000 cm-1 (2.0-2.5 microns). Calibration models based on a simple univariate calibration procedure are not capable of providing accurate glucose concentrations from an independent set of prediction spectra. By use of the multivariate technique of partial least squares (PLS) regression, glucose concentrations can be determined with a 0.35 mM (6.3 mg/dL) standard error of prediction. The spectral range for this calibration model extends from 4600 to 4200 cm-1, and the optimum number of PLS factors is 14. In addition, calibration models based on a combination of digital Fourier filtering and PLS regression have been constructed and evaluated. Superior calibration models are obtained by using a preprocessing digital filtering step to remove spectral features not associated with glucose. The best overall calibration model was obtained by using a Gaussian-shaped Fourier filter defined by a mean position of 0.03f and standard deviation of 0.007f coupled with a 12-factor PLS regression computed over the spectral range from 4600 to 4200 cm-1. This model provided a standard error of prediction of 0.24 mM (4.3 mg/dL) for an independent set of prediction spectra.(ABSTRACT TRUNCATED AT 250 WORDS)

Blood Glucose↗

PubMed1993

Strategies for coupling digital filtering with partial least-squares regression: application to the determination of glucose in plasma by Fourier transform near-infrared spectroscopy.

Protocols are established for coupling digital filtering techniques with partial least-squares (PLS) regression for use in constructing multivariate calibration models from Fourier transform near-infrared absorbance spectra. Calibration models are developed to predict glucose concentrations in bovine plasma samples. Employing a calibration data set of 300 spectra collected from 55 plasma samples and 3 plasma lots, individual calibration models are developed based on four spectral ranges selected from the region 5000-4000 cm-1. A separate test set of 69 spectra collected from 14 plasma samples is used to evaluate the computed models. Gaussian-shaped bandpass digital filters are implemented by use of Fourier filtering techniques and employed to preprocess spectra to remove variation due to the background absorbance of the plasma matrix. PLS regression is used with the filtered spectra to compute calibration models for glucose. The optimization of the filter bandpass parameters is explored through the use of response surface methods. Through these optimization studies, calibration models are developed that achieve standard errors of estimate and standard errors of prediction in the range 0.4-0.5 mM across the concentration range of 2.5-25.5 mM. It is determined that the use of digital filtering as a preprocessing step significantly improves the performance of the resulting calibration models, minimizes the importance of spectral range in the calibration model development, and reduces the required number of PLS factors in each model.

Animals↗

PubMed1992

Fiber-optic ammonia sensor for measuring synaptic glutamate and extracellular ammonia.

A fiber-optic ammonia gas sensor designed for neurochemical applications is presented. Parameters evaluated in terms of effect on the steady-state and dynamic response of this sensor include the indicator dye, concentrations of indicator and total ammonia nitrogen in the internal solution, volume of the internal solution, structure of the gas-permeable membrane, and temperature. The final ammonia sensor responds over the concentration range from 7 to 3000 nM with a limit of detection of 7 nM and response times ranging from 2 to 5 min. Glutamate oxidase is immobilized at the tip of this ammonia sensor to provide a glutamate biosensor with a detection limit of 0.1 microM when operated at pH 7.8. In addition, this ammonia sensor is used to measure extracellular ammonia levels in perfused retinal and eye-cup tissue preparations. These measurements indicate a calcium-dependent, potassium-evoked release of ammonia during these depolarization conditions.

Ammonia↗

PubMed1992

Dual-enzyme fiber-optic biosensor for glutamate based on reduced nicotinamide adenine dinucleotide luminescence.

Response characteristics are presented for a dual-enzyme fiber-optic biosensor for glutamate. An enzyme layer composed of glutamate dehydrogenase (GDH) and glutamate-pyruvate transaminase (GPT) is used to produce reduced nicotinamide adenine dinucleotide (NADH) at the tip of a fiber-optic probe. NADH luminescence is monitored through this probe and the measured fluorescence intensity is related to the concentration of glutamate. GDH catalyzes the formation of NADH, and GPT drives the GDH reaction by removing a reaction product and regenerating glutamate. Optimal response is obtained in a pH 7.4 Tris-HCl buffer maintained at 25 degrees C in the presence of 4 mM NAD+ and 10 mM L-alanine. The temperature profile reveals a strong negative temperature effect which is attributed to the temperature dependency of NADH luminescence. Under optimal conditions, the sensor sensitivity is 0.127 nA/microM over the 1-10 microM concentration range, the detection limit is 0.13 microM, and response times range from 4 to 8 min. The sensor response is stable for 12 days when stored at 4 degrees C. Selectivity for glutamate is excellent over most of the common amino acids as well as ascorbic acid, uric acid, taurine, and GABA. Only slight responses were observed for glutamine and lysine. The effect of ammonia on the glutamate response was found to be minimal at total ammonia nitrogen concentrations as high as 200 microM.

Biosensing Techniques↗

PubMed1992

Measurement of water sorption by resin composite adhesives with near-infrared spectroscopy.

Spectroscopic methodology was used to follow the water uptake of disks of two resin composite luting agents during long-term storage. Fourier-transform near-infrared (FT-NIR) spectroscopy was used for collection of spectra over the 4200-6500 cm-1 spectral region. The 5200-cm-1 absorption band of water was monitored initially, at 24 h, seven days, two weeks, and then monthly over a period of 12 months. The disks were stored in water, air, and desiccated conditions. Disks were also subjected to two alternate cycles (two weeks each) of hydration and desiccation. A spectral manipulation program was used for quantitation of the area under the water absorbance band. Area ratios demonstrated similar water-uptake patterns for the two adhesives. Rapid water uptake was seen within the first two weeks of storage. Alternate hydration and desiccation of the samples showed that water uptake by the filler/polymer network was partially reversible. The desiccant was unable to remove all the water from the samples, which indicated that some water was tightly held within the sample matrix. FT-NIR spectroscopy is recommended as an effective method for study of the equilibration of resin composites in water.

Absorption↗