David M. Haaland

Multivariate classification of infrared spectra of cell and tissue samples

Infrared microspectroscopy of biopsied canine lymph cells and tissue was performed to investigate the possibility of using IR spectra coupled with multivariate classification methods to classify the samples as normal, hyperplastic, or neoplastic (malignant). IR spectra were obtained in transmission mode through BaF2 windows and in reflection mode from samples prepared on gold-coated microscope slides. Cytology and histopathology samples were prepared by a variety of methods to identify the optimal methods of sample preparation. Cytospinning procedures that yielded a monolayer of cells on the BaF2 windows produced a limited set of IR transmission spectra. These transmission spectra were converted to absorbance and formed the basis for a classification rule that yielded 100% correct classification in a cross-validated context. Classifications of normal, hyperplastic, and neoplastic cell sample spectra were achieved by using both partial least-squares (PLS) and principal component regression (PCR) classification methods. Linear discriminant analysis applied to principal components obtained from the spectral data yielded a small number of misclassifications. PLS weight loading vectors yield valuable qualitative insight into the molecular changes that are responsible for the success of the infrared classification. These successful classification results show promise for assisting pathologists in the diagnosis of cell types and offer future potential for in vivo IR detection of some types of cancer.

Multivariate Least-Squares Methods Applied to the Quantitative Spectral Analysis of Multicomponent Samples

In an extension of earlier work, weighted multivariate least-squares methods of quantitative FT-IR analysis have been developed. A linear least-squares approximation to nonlinearities in the Beer-Lambert law is made by allowing the reference spectra to be a set of known mixtures. The incorporation of nonzero intercepts in the relation between absorbance and concentration further improves the approximation of nonlinearities while simultaneously accounting for nonzero spectral baselines. Pathlength variations are also accommodated in the analysis, and under certain conditions, unknown sample pathlengths can be determined. All spectral data are used to improve the precision and accuracy of the estimated concentrations. During the calibration phase of the analysis, pure component spectra are estimated from the standard mixture spectra. These can be compared with the measured pure component spectra to determine which vibrations experience nonlinear behavior. In the predictive phase of the analysis, the calculated spectra are used in our previous least-squares analysis to estimate sample component concentrations. These methods were applied to the analysis of the IR spectra of binary mixtures of esters. Even with severely overlapping spectral bands and nonlinearities in the Beer-Lambert law, the average relative error in the estimated concentrations was <1%.

Improved sensitivity of infrared spectroscopy by the application of least squares methods

Improved sensitivity and precision in the quantitative analysis of trace gases by Fourier transform infrared spectroscopy have been achieved by the application of new spectral least squares methods. By relating all of the spectral information present in the reference spectrum of a trace gas to that of the unknown sample and by appropriately fitting the baseline, detections of trace gases can be obtained even though the individual spectral features may lie well below the noise level. Four least squares methods incorporating different baseline assumptions were investigated and compared using calibrated gases of CO, N2O, and CO2 in dry air. These methods include: (I) baseline known, (II) baseline linear over the spectral region of interest, (III) baseline linear over each spectral peak, and (IV) negligible baseline shift between successive data points. Methods III and IV were found to be most reliable for the gases studied. When method III is applied to the spectra of these trace gases, detection limits improved by factors of 5 to 7 over conventional methods applied to the same data. “Three sigma” detection limits are equal to 0.6, 0.2, and 0.08 ppm for CO, N2O, and CO2, respectively, when a 10-cm pathlength at a total pressure of 640 Torr is used with a ∼35 min measurement time at 0.06 cm−1 resolution.

Application of New Least-Squares Methods for the Quantitative Infrared Analysis of Multicomponent Samples

Improvements have been made in previous least-squares regression analyses of infrared spectra for the quantitative estimation of concentrations of multicomponent mixtures. Spectral baselines are fitted by least-squares methods, and overlapping spectral features are accounted for in the fitting procedure. Selection of peaks above a threshold value reduces computation time and data storage requirements. Four weighted least-squares methods incorporating different baseline assumptions were investigated using FT-IR spectra of the three pure xylene isomers and their mixtures. By fitting only regions of the spectra that follow Beers Law, accurate results can be obtained using three of the fitting methods even when baselines are not corrected to zero. Accurate results can also be obtained using one of the fits even in the presence of Beers Law deviations. This is a consequence of pooling the weighted results for each spectral peak such that the greatest weighting is automatically given to those peaks that adhere to Beers Law. It has been shown with the xylene spectra that semiquantitative results can be obtained even when all the major components are not known or when expected components are not present. This improvement over previous methods greatly expands the utility of quantitative least-squares analyses.

Kinetics of dissociative chemisorption on strained edge-shared surface defects on dehydroxylated silica

Abstract Fourier transform infrared (FTIR) spectroscopy is used to study the kinetics of reactions between water, ammonia, methanol, and methylamine and the edge-shared tetrahedral surface defects in dehydroxylated silica. Results show that all reactant gases tested undergo a dissociative chemisorption reaction on strained SiO bonds in the edge-shared ring. The reaction kinetics and observed product distributions indicate that two types of edge-shared rings are present, one which contains silanol groups and one which does not. The silanol-containing defects are less reactive than the silanol-free defects, with reaction rates which are more sensitive to the basicity of the gas phase reactant. The rate of reaction between water and defects is at least 100000 faster than the hydrolysis of unstrained SiO bonds. The relative reactivities of strained and unstrained Si-O bonds show that bond strain promotes bond rupture reactions which are important in phenomena such as the stress corrosion cracking of silica.

In vivo hyperspectral confocal fluorescence imaging to determine pigment localization and distribution in cyanobacterial cells

Hyperspectral confocal fluorescence imaging provides the opportunity to obtain individual fluorescence emission spectra in small (≈0.03-μm3) volumes. Using multivariate curve resolution, individual fluorescence components can be resolved, and their intensities can be calculated. Here we localize, in vivo, photosynthesis-related pigments (chlorophylls, phycobilins, and carotenoids) in wild-type and mutant cells of the cyanobacterium Synechocystis sp. PCC 6803. Cells were excited at 488 nm, exciting primarily phycobilins and carotenoids. Fluorescence from phycocyanin, allophycocyanin, allophycocyanin-B/terminal emitter, and chlorophyll a was resolved. Moreover, resonance-enhanced Raman signals and very weak fluorescence from carotenoids were observed. Phycobilin emission was most intense along the periphery of the cell whereas chlorophyll fluorescence was distributed more evenly throughout the cell, suggesting that fluorescing phycobilisomes are more prevalent along the outer thylakoids. Carotenoids were prevalent in the cell wall and also were present in thylakoids. Two chlorophyll fluorescence components were resolved: the short-wavelength component originates primarily from photosystem II and is most intense near the periphery of the cell; and the long-wavelength component that is attributed to photosystem I because it disappears in mutants lacking this photosystem is of higher relative intensity toward the inner rings of the thylakoids. Together, the results suggest compositional heterogeneity between thylakoid rings, with the inner thylakoids enriched in photosystem I. In cells depleted in chlorophyll, the amount of both chlorophyll emission components was decreased, confirming the accuracy of the spectral assignments. These results show that hyperspectral fluorescence imaging can provide unique information regarding pigment organization and localization in the cell.

Post-Prandial Blood Glucose Determination by Quantitative Mid-Infrared Spectroscopy

The multivariate calibration method of partial least-squares (PLS) was applied to the mid-infrared spectra of whole blood for quantitatively determining blood glucose concentrations. Separate calibration models were developed on the basis of spectra of whole blood obtained from six diabetic subjects from either in vitro glucose-supplemented blood or blood obtained from the same subjects in the post-prandial state during meal tolerance tests. The cross-validated PLS calibrations yielded average errors in glucose concentration of 11 and 13 mg/dL, respectively. It is desirable to use the calibration models based on the in vitro glucose-supplemented blood for determining glucose concentrations in unknown blood samples. However, when these multivariate calibration models based upon in vitro blood spectra were applied to the spectra of the postprandial blood samples, a subject-dependent concentration bias was observed. The source of this bias was not identified, but when the glucose determinations were corrected for the bias, average concentration errors were found to be 14 mg/dL. Changes in spectrometer design or calibrations based on large numbers of subjects are expected to eliminate the presence of this bias. If these measures do not succeed in eliminating the bias, then methods are demonstrated that significantly reduce the bias while retaining the sensitive outlier detection capabilities of the PLS methods. These latter methods require that the infrared spectrum and reference glucose levels be obtained from a single blood sample from each subject.

Hyperspectral confocal microscope.

We have developed a new, high performance, hyperspectral microscope for biological and other applications. For each voxel within a three-dimensional specimen, the microscope simultaneously records the emission spectrum from 500 nm to 800 nm, with better than 3 nm spectral resolution. The microscope features a fully confocal design to ensure high spatial resolution and high quality optical sectioning. Optical throughput and detection efficiency are maximized through the use of a custom prism spectrometer and a backside thinned electron multiplying charge coupled device (EMCCD) array. A custom readout mode and synchronization scheme enable 512-point spectra to be recorded at a rate of 8300 spectra per second. In addition, the EMCCD readout mode eliminates curvature and keystone artifacts that often plague spectral imaging systems. The architecture of the new microscope is described in detail, and hyperspectral images from several specimens are presented.

Infrared spectra of edge-shared silicate tetrahedra

Abstract Dehydroxylated silica exhibits two well-defined infrared bands at 888 and 907 cm−1 previously assigned to a highly reactive strained surface defect. Comparisons of the spectra of dehydroxylated silica to frequencies and intensities calculated using molecular orbital (MO) calculations and to spectra obtained for cyclodisiloxanes suggest that the strained surface defect consists of an edge-shared silicate tetrahedral ring. Changes in vibrational frequencies and peak intensities with 18O labeling for both the surface defect and the cyclodisiloxanes are consistent with those expected for ring vibrational modes. The IR bands associated with the strained edge-shared ring disappear when either the surface defects or the cyclodisiloxanes react with water. Reactions of the surface defect can be used to study how strain enhances the reactivity of Si-O-Si bonds for modeling phenomena such as stress corrosion cracking.

New prediction-augmented classical least squares (PACLS) methods: Application to unmodeled interferents

A significant improvement to the classical least-squares (CLS) multivariate analysis method has been developed. The new method, called prediction-augmented classical least-squares (PACLS), removes the restriction for CLS that all interfering spectral species must be known and their concentrations included during the calibration. We demonstrate that PACLS can correct inadequate CLS models if spectral components left out of the calibration can be identified and if their “spectral shapes” can be derived and added during a PACLS prediction step. The new PACLS method is demonstrated for a system of dilute aqueous solutions containing urea, creatinine, and NaCl analytes with and without temperature variations. We demonstrate that if CLS calibrations are performed with only a single analytes concentrations, then there is little, if any, prediction ability. However, if pure-component spectra of analytes left out of the calibration are independently obtained and added during PACLS prediction, then the CLS prediction ability is corrected and predictions become comparable to that of a CLS calibration that contains all analyte concentrations. It is also demonstrated that constant-temperature CLS models can be used to predict variable-temperature data by employing the PACLS method augmented by the spectral shape of a temperature change of the water solvent. In this case, PACLS can also be used to predict sample temperature with a standard error of prediction of 0.07 °C even though the calibration data did not contain temperature variations. The PACLS method is also shown to be capable of modeling system drift to maintain a calibration in the presence of spectrometer drift.