Determination of physiological levels of glucose in an aqueous matrix with digitally filtered Fourier transform near-infrared spectra

A procedure is described for the measurement of clinically relevant concentrations of glucose in aqueous solutions with near-infrared (NIR) absorbance spectroscopy. A glucose band centered at 4400 cm-1 is used for this analysis. NIR spectra are collected over the frequency range 5000-4000 cm-1 with a Fourier transform spectrometer. A narrow-band-pass optical interference filter is placed in the optical path of the spectrometer to eliminate light outside this restricted range. This configuration provides a 2.9-fold reduction in spectral noise by utilizing the dynamic range of the detector solely for light transmitted through the filter. In addition, a novel spectral processing scheme is described for extracting glucose concentration information from the resulting absorbance spectra. The key component of this scheme is a digital Fourier filter that removes both high-frequency noise and low-frequency base-line variations from the spectra. Numerical optimization procedures are used to identify the best location and width of a Gaussian-shaped frequency response function for this Fourier filter. A dynamic area calculation, coupled with a simple linear base-line correction, provides an integrated area from the processed spectra that is linearly related to glucose concentrations over the range 1-20 mM. The linear calibration model accurately predicted glucose levels in a series of test solutions with an overall mean percent error of 2.5%. Based on the uncertainty in the parameters defining the calibration model and the variability of the magnitudes of the integrated areas, an overall uncertainty of 7.8% was estimated for predicted glucose concentrations.     

Calibration of multiplexed fiber-optic spectroscopy

Large-scale commercial bioprocesses that manufacture biopharmaceutical products such as monoclonal antibodies generally involve multiple bioreactors operated in parallel. Spectra recorded during in situ monitoring of multiple bioreactors by multiplexed fiber-optic spectroscopies contain not only spectral information of the chemical constituents but also contributions resulting from differences in the optical properties of the probes. Spectra with variations induced by probe differences cannot be efficiently modeled by the commonly used multivariate linear calibration models or effectively removed by popular empirical preprocessing methods. In this study, for the first time, a calibration model is proposed for the analysis of complex spectral data sets arising from multiplexed probes. In the proposed calibration model, the spectral variations introduced by probe differences are explicitly modeled by introducing a multiplicative parameter for each optical probe, and then their detrimental effects are effectively mitigated through a "dual calibration" strategy. The performance of the proposed multiplex calibration model has been tested on two multiplexed spectral data sets (i.e., MIR data of ternary mixtures and NIR data of bioprocesses). Experimental results suggest that the proposed calibration model can effectively mitigate the detrimental effects of probe differences and hence provide much more accurate predictions than commonly used multivariate linear calibration models (such as PLS) with and without empirical data preprocessing methods such as orthogonal signal correction, standard normal variate, or multiplicative signal correction.     

Extension of fourier transform vibrational circular dichroism into the near-infrared region: continuous spectral coverage from 800 to 10 000 cm(-1)

We report the first vibrational circular dichroism (VCD) spectra with continuous coverage from 800 cm(-1) in the mid-infrared (MIR) region to 10 000 cm(-1) in the near-infrared (NIR) region. This coverage is illustrated with MIR and NIR absorbance and VCD spectra of 2,2-dimethyl-dioxolane-4-methanol (DDM), alpha-pinene, and camphor that serve as calibration samples over this entire region. Commercially available, dual-source Fourier transform (FT) MIR and NIR VCD spectrometers were equipped with appropriate light sources, optics, and detectors, and were modified for dual-polarization-modulation (DPM) operation. The combination of liquid-nitrogen- and thermoelectric-cooled HgCdTe (MCT) detectors, as well as InGaAs and Germanium (Ge) detectors operating at room temperature, permitted collection of the desired absorbance and VCD spectra across the range of vibrational fundamental, combination band, and overtone frequencies. The spectra of DDM and alpha-pinene were measured as neat liquids and recorded for both enantiomers in the various spectral regions. Spectra for camphor were all measured in CCl(4) solution at a concentration of 0.6 M, except for the carbonyl-stretching region, where a more dilute concentration was used. The typical anisotropy ratios (g) of the three molecules were estimated with respect to their strongest VCD bands in each spectral region. It was found that for all three molecules in the spectral regions above 2000 cm(-1), anisotropy ratios are approximately the same order (10(-5)) of magnitude. However, in the MIR region, the typical anisotropy ratios are significantly different for the three molecules. This study demonstrates that with modern FT-VCD spectrometers modified for DPM operation, VCD spectra can be measured continuously across a wide spectral range from the MIR to nearly the visible region with an unsurpassed combination of signal-to-noise ratio and spectral resolution.     

Temperature-insensitive near-infrared method for determination of protein concentration during protein crystal growth

A temperature-insensitive method for measuring protein concentration in aqueous solutions using near-infrared spectroscopy is described. The method, which is based on identification of the net analyte signal of single-beam spectra, can be calibrated using a single protein absorbance measurement and is thus well suited for crystallization monitoring where the quantity of protein is limited. The method is applied to measurements of glucose-isomerase concentration in a sodium phosphate buffer that is actively varied over the temperature range of 4-24 degrees C. The standard error of prediction using the optimized spectral range of 4670-4595 cm(-1) is 0.12 mg/mL with no systematic trend in the residuals with solution temperature. The method is also applied to previously collected spectra of hen egg-white lysozyme and yields a standard error of prediction of 0.14 mg/mL. Spectra sampled at discrete wavelengths can also be used for calibration and prediction with performance comparable to that obtained with spectral bands. A set of four wavelengths are identified that can be used to predict concentrations of both proteins with a standard error less than 0.14 mg/mL.     

Exploring time-dependent structural changes during the cold crystallization process of isotactic polystyrene by infrared spectroscopy and multivariate curve resolution

The present study attempts an application of Fourier transform infrared (FT-IR) spectroscopy in conjunction with multivariate curve resolution (MCR) techniques to explore the structural evolution of isotactic polystyrene (iPS) during the cold crystallization process. The focus of the present study is placed on the performance of MCR techniques, e.g., orthogonal projection (OP), alternating least squares (ALS), and fixed-size moving window evolving factor analysis (FSMWEFA), and the interpretability of spectral changes in the investigated chemical process. As a result, valuable information and conclusions about the structural evolution of iPS during the crystallization process can be extracted: when the amorphous phase of iPS changes, the ordering of the phenyl rings takes place first, and then the polymer chains adjust their local conformations to form short 3(1) helix structures. Furthermore, according to intensity profiles of the spectral variations, the ordering of the phenyl rings proceeds more intensely than the formation of ordered local chains, and the structural evolution of iPS occurs even during the induction period. The spectral variations resulting from the conformational changes in the 3(1) helical structures depend on the sequence length of the helical chains: the longer the polymer chain is, the smaller the corresponding band variations are. It has been demonstrated that the combination of FTIR spectroscopy and chemometric MCR techniques is very promising for the analysis of the crystallization process of polymers. MCR is a powerful tool for analyzing and visualizing spectral data and integrating them with other information, making spectral intensity variations more amenable to interpretation in order to explore the molecular dynamics of polymers.     

Polarized Raman microspectroscopy can reveal structural changes of peritumoral dermis in basal cell carcinoma

Polarized Raman microspectroscopy can provide precious information regarding the orientation and ordering of the molecules in a sample without staining or particular preparation. This technique is used for the first time on a human skin section to probe the molecular modifications of the surrounding dermis in superficial basal cell carcinoma. Spectra using polarized and conventional Raman microspectroscopies were recorded on dermis bordering either the tumor or healthy epidermis. Band areas and spectral decomposition on selected vibrations were computed. Significant differences in dermal collagen vibration bands are detected using both polarized and conventional micro-spectroscopies, but the spectral changes between tumor and healthy tissues are enhanced using polarized Raman microspectroscopy. The analysis of these spectral differences highlights structural modifications of the triple helix of collagen. We see polarized Raman microspectroscopy as a potential tool that could be implemented for clinical analyses to guide clinicians and surgeons in the treatment of aggressive skin cancers. The information obtainable could also help better elucidate the molecular mechanisms induced in basal cell carcinoma development.     

Spectral prediction model for piles of nonscattering sheets

The present paper investigates the reflection and transmission properties of piles of nonscattering sheets. Using a spectral prediction model, we perform a detailed analysis of the spectral and color variations induced by variations of the number of superposed sheets, the absorbance of the sheet material, the refractive index of the medium between the sheets, and the reflectance of the background. The spectral prediction model accounts for the multiple reflections and transmissions of light between the interfaces bounding the layers. We describe in detail the procedure for deducing model parameters from measured data. Tests performed with nonscattering plastic sheets demonstrate the excellent accuracy of the predictions. A large set of predicted spectra illustrate the different evolutions of reflected and transmitted spectra as well as the corresponding colors for various types of piles.     

Removal of analyte-irrelevant variations in near-infrared tissue spectra

This paper describes mathematical techniques to correct for analyte-irrelevant optical variability in tissue spectra by combining multiple preprocessing techniques to address variability in spectral properties of tissue overlying and within the muscle. A mathematical preprocessing method called principal component analysis (PCA) loading correction is discussed for removal of inter-subject, analyte-irrelevant variations in muscle scattering from continuous-wave diffuse reflectance near-infrared (NIR) spectra. The correction is completed by orthogonalizing spectra to a set of loading vectors of the principal components obtained from principal component analysis of spectra with the same analyte value, across different subjects in the calibration set. Once the loading vectors are obtained, no knowledge of analyte values is required for future spectral correction. The method was tested on tissue-like, three-layer phantoms using partial least squares (PLS) regression to predict the absorber concentration in the phantom muscle layer from the NIR spectra. Two other mathematical methods, short-distance correction to remove spectral interference from skin and fat layers and standard normal variate scaling, were also applied and/or combined with the proposed method prior to the PLS analysis. Each of the preprocessing methods improved model prediction and/or reduced model complexity. The combination of the three preprocessing methods provided the most accurate prediction results. We also performed a preliminary validation on in vivo human tissue spectra.     

Determination of glucose concentration in a scattering medium based on selected wavelengths by use of an overtone absorption band

A method and device for measuring glucose concentration in a scattering medium have been developed. A spectral range of 800-1800 nm is considered for wavelength selection because of its deeper penetration into biological tissue and the presence of a glucose absorption band. An algorithm based on selected wavelengths is proposed to minimize interference from other components. The optimal distance between the light source and the detector for diffuse reflectance measurement minimizes the influence of medium scattering. The proposed algorithm and measuring device are tested with a solution containing milk with added glucose. Glucose concentrations between 0 and 2000 mg/dl are determined with a correlation coefficient of 0.977. We also investigate the influence of concentration variations of other substances such as water, hemoglobin, albumin, and cholesterol when they are mixed in a scattering medium.     

Molar absorptivities of glucose and other biological molecules in aqueous solutions over the first overtone and combination regions of the near-infrared spectrum

Molar absorptivities are measured for water, glucose, alanine, ascorbate, lactate, triacetin, and urea in the near-infrared spectral region at 37 degrees C. Values are based on the Beer-Lambert law and cover the first overtone (1550-1850 nm; 6450-5400 cm(-1)) and combination (2000-2500 nm; 4000-5000 cm(-1)) spectral windows through aqueous media. Accurate calculations demand accounting for the impact of water displacement upon dissolution of solute. In this regard, water displacement coefficients are measured and reported for each solute. First overtone absorptivities range from 2 to 7 x 10(-5) mM(-1)mm(-1) for all solutes except urea, for which absorptivity values are below 0.5 x 10(-5) mM(-1) mm(-1) across this spectral range. Molar absorptivities over the combination spectral region range from 0.8 to 3.2 x 10(-4) mM(-1) mm(-1), which is a factor of four to five greater than the first overtone absorptivities. Accuracy of the measured values is assessed by comparing calculated or modeled spectra with spectra measured from standard solutions. This comparison reveals accurately modeled spectra in terms of magnitude and position of solute absorption bands. Both actual and modeled spectra from glucose solutions reveal positive and negative absorbance values depending on the measurement wavelength. It is shown that the net absorbance of light is controlled by the magnitude of the absorptivity of glucose compared to the product of the absorptivity of water and the water displacement coefficient for glucose.     

The effect of microroughness of the optical properties of deposited chromium films

A polarization modulation technique was used to monitor continuously changes in the absorbance of optically opaque chromium films during vapour deposition in an ultrahigh vacuum. Qualitatively reproducible changes in the absorbance are attributed to variations in the surface microroughness during deposition.     

On-line near-infrared spectrometer to monitor urea removal in real time during hemodialysis

The ex vivo removal of urea during hemodialysis treatments is monitored in real time with a noninvasive near-infrared spectrometer. The spectrometer uses a temperature-controlled acousto optical tunable filter (AOFT) in conjunction with a thermoelectrically cooled extended wavelength InGaAs detector to provide spectra with a 20 cm(-1) resolution over the combination region (4000-5000 cm(-1)) of the near-infrared spectrum. Spectra are signal averaged over 15 seconds to provide root mean square noise levels of 24 micro-absorbance units for 100% lines generated over the 4600-4500 cm(-1) spectral range. Combination spectra of the spent dialysate stream are collected in real-time as a portion of this stream passes through a sample holder constructed from a 1.1 mm inner diameter tube of Teflon. Real-time spectra are collected during 17 individual dialysis sessions over a period of 10 days. Reference samples were extracted periodically during each session to generate 87 unique samples with corresponding reference concentrations for urea, glucose, lactate, and creatinine. A series of calibration models are generated for urea by using the partial least squares (PLS) algorithm and each model is optimized in terms of number of factors and spectral range. The best calibration model gives a standard error of prediction (SEP) of 0.30 mM based on a random splitting of spectra generated from all 87 reference samples collected across the 17 dialysis sessions. PLS models were also developed by using spectra collected in early sessions to predict urea concentrations from spectra collected in subsequent sessions. SEP values for these prospective models range from 0.37 mM to 0.52 mM. Although higher than when spectra are pooled from all 17 sessions, these prospective SEP values are acceptable for monitoring the hemodialysis process. Selectivity for urea is demonstrated and the selectivity properties of the PLS calibration models are characterized with a pure component selectivity analysis.     

Scattering and absorption effects in the determination of glucose in whole blood by near-infrared spectroscopy

Optical properties of whole bovine blood are examined under conditions of different glucose loadings. A strong dependency is established between the scattering properties of the whole blood matrix and the concentration of glucose. This dependency is explained in terms of variations in the refractive index mismatch between the scattering bodies (predominately red blood cells) and the surrounding plasma. Measurements in the presence of a well-known glucose transport inhibitor indicate that variations in refractive index mismatch are related to the penetration of glucose into the red blood cells and demonstrate that increased scattering involves the uptake of glucose by red blood cells. Finally, multivariate calibration models are presented for the measurement of glucose in a whole blood matrix. These models are based on near-infrared spectral data collected from 80 different samples prepared from a single whole blood matrix. Calibration studies are performed over the combination, first-overtone, and short-wavelength spectral regions. The best calibration model is generated from combination region spectra, providing a standard error of prediction (SEP) of less than 1 mM over the concentration range of 3-30 mM. The model based on the first-overtone region is slightly degraded but still provides acceptable performance (SEP = 1.20 mM). The model based on the short-wavelength region is further degraded (SEP = 2.53 mM). To rationalize these results, an analysis of the selectivity of the calibration models is performed by computing the glucose net analyte signal. It is established that the models based on the combination and first-overtone regions are dominated by glucose absorption information, while the model computed from the short-wavelength region is based primarily on scattering information. This result provides evidence that absorption information is needed in order to obtain a glucose calibration model with acceptable performance.     

Noninvasive in vivo measurement of venous blood pH during exercise using near-infrared reflectance spectroscopy

Blood pH is an important indicator of anaerobic metabolism in exercising muscle. This paper demonstrates multivariate calibration techniques that can be used to produce a general pH model that can be applied to spectra from any new subject without significant prediction error. Tissue spectra (725 approximately 880 nm) were acquired through the skin overlying the flexor digitorum profundus muscle on the forearms of eight healthy subjects during repetitive hand-grip exercise and referenced to the pH of venous blood drawn from a catheter placed in a vein close to the muscle. Calibration models were developed using multi-subject partial least squares (PLS) and validated using subject-out cross-validation after the subject-to-subject spectral variations were corrected by mathematical preprocessing methods. A combination of standard normal variate (SNV) scaling and principal component analysis loading correction (PCALC) successfully removed most of the subject-to-subject variations and provided the most accurate prediction results.     

Pure component selectivity analysis of multivariate calibration models from near-infrared spectra

A novel procedure is proposed as a method to characterize the chemical basis of selectivity for multivariate calibration models. This procedure involves submitting pure component spectra of both the target analyte and suspected interferences to the calibration model in question. The resulting model output is analyzed and interpreted in terms of the relative contribution of each component to the predicted analyte concentration. The utility of this method is illustrated by an analysis of calibration models for glucose, sucrose, and maltose. Near-infrared spectra are collected over the 5000-4000-cm(-)(1) spectral range for a set of ternary mixtures of these sugars. Partial least-squares (PLS) calibration models are generated for each component, and these models provide selective responses for the targeted analytes with standard errors of prediction ranging from 0.2 to 0.7 mM over the concentration range of 0.5-50 mM. The concept of the proposed pure component selectivity analysis is illustrated with these models. Results indicate that the net analyte signal is solely responsible for the selectivity of each individual model. Despite strong spectral overlap for these simple carbohydrates, calibration models based on the PLS algorithm provide sufficient selectivity to distinguish these commonly used sugars. The proposed procedure demonstrates conclusively that no component of the sucrose or maltose spectrum contributes to the selective measurement of glucose. Analogous conclusions are possible for the sucrose and maltose calibration models.     

Structural changes in the cells of some bacteria during population growth: a Fourier transform infrared-attenuated total reflectance study

Structural changes occurring in the cells of several bacteria during their growth curves have been investigated by Fourier transform infrared (FT-IR) spectroscopy using the sampling technique of attenuated total reflectance (ATR). Spectra reflect all of the components of the cells, including the cell walls, cell membranes, internal structures, and the cytoplasm. The bacteria studied were Bacillus stearothermophilus, Halobacterium salinarum, Halococcus morrhuae, and Acetobacter aceti. All species showed significant spectral changes during their growth curves, indicating structural changes in the cells during increases in cell numbers. The major change for B. stearothermophilus was in the lipid content, which was at a maximum during the exponential phase of the growth curve. For the halophiles H. salinarum and H. morrhuae, the major change was that the concentration of sulfate ion in the cells varied during the growth curve and was at a maximum during the mid-part of the exponential phase of the growth curve. A. aceti cells showed increasing polysaccharide content during the growth curve as well as maximum lipid content during the exponential phase of growth.     

Use of the orthogonal projection approach (OPA) to monitor batch processes

The orthogonal projection approach (OPA) and multivariate curve resolution (MCR) are presented as a way to monitor batch processes using spectroscopic data. Curve resolution allows one to look within a batch and predict on-line real concentration profiles of the different species appearing during reactions. Taking into account the variations of the process by using an augmented matrix of complete batches, the procedure explained here calculates some prediction coefficients that can afterwards be applied for a new batch.     

Visible reflectance hyperspectral imaging: characterization of a noninvasive,in vivo system for determining tissue perfusion

We characterize a visible reflectance hyperspectral imaging system for noninvasive, in vivo, quantitative analysis of human tissue in a clinical environment. The subject area is illuminated with a quartz-tungsten-halogen light source, and the reflected light is spectrally discriminated by a liquid crystal tunable filter (LCTF) and imaged onto a silicon charge-coupled device detector. The LCTF is continuously tunable within its useful visible spectral range (525-725 nm) with an average spectral full width at half-height bandwidth of 0.38 nm and an average transmittance of 10.0%. A standard resolution target placed 5.5 ft from the system results in a field of view with a 17-cm diameter and an optimal spatial resolution of 0.45 mm. The measured reflectance spectra are quantified in terms of apparent absorbance and formatted as a hyperspectral image cube. As a clinical example, we examine a model of vascular dysfunction involving both ischemia and reactive hyperemia during tissue reperfusion. In this model, spectral images, based upon oxyhemoglobin and deoxyhemoblobin signals in the 525-645-nm region, are deconvoluted using a multivariate least-squares regression analysis to visualize the spatial distribution of the percentages of oxyhemoglobin and deoxyhemoglobin in specific skin tissue areas.     

Responses of hydrophobic and hydrophilic groups in Nafion differentiated by least squares modeling of infrared spectra recorded during thin film hydration

Least squares modeling was applied to gain insights into changes that occur in the structure of Nafion polymer membrane during hydration. Transmission infrared spectra followed changes in the strong polymer bands in the range of 1400-950 cm(-1) during water uptake by initially dry membrane upon exposure to 100% relative humidity atmosphere. Spectra recorded during hydration were fit to a rate equation that modeled the loss of a dry state accompanied by the development of a hydrated state. The evolution of the two states was described by an equation for diffusion in a cylindrical pore in the long time limit. Comparison of the experimental spectra in a data set to spectra calculated from the pure components derived by least squares modeling gave an excellent match for bands of the -CF2 and C-O-C group modes, but agreement was not as close for bands arising from modes of the hydrophilic -SO3(-) group and (modeled separately) water. The differences are discussed in terms of the likelihood that the -SO3(-) groups have stronger interactions with bulk-like water condensed in the membrane and therefore undergo more complex changes than do more hydrophobic polymer regions during hydration. A different model is necessary to describe the evolution of spectral features for water and -SO3(-) end groups during water uptake into Nafion thin films.     

Highlight detection and removal from spectral image

We present a constrained spectral unmixing method to remove highlight from a single spectral image. In the constrained spectral unmixing method, the constraints have been imposed so that all the fractions of diffuse and highlight reflection sum up to 1 and are positive. As a result, the spectra of the diffuse image are always positive. The spectral power distribution (SPD) of the light source has been used as the pure highlight spectrum. The pure diffuse spectrum of the measured spectrum has been chosen from the set of diffuse spectra. The pure diffuse spectrum has a minimum angle among the angles calculated between spectra from a set of diffuse spectra and the measured spectrum projected onto the subspace orthogonal to the SPD of the light source. The set of diffuse spectra has been collected by an automated target generation program from the diffuse part in the image. Constrained energy minimization in a finite impulse response linear filter has been used to detect the highlight and diffuse parts in the image. Results by constrained spectral unmixing have been compared with results by the orthogonal subspace projection (OSP) method [Proceedings of International Conference on Pattern Recognition (2006), pp. 812-815] and probabilistic principal component analysis (PPCA) [Proceedings of the 4th WSEAS International Conference on Signal Processing, Robotics and Automation (2005), paper 15]. Constrained spectral unmixing outperforms OSP and PPCA in the visual assessment of the diffuse results. The highlight removal method by constrained spectral unmixing is suitable for spectral images.