Multicomponent blood analysis by near-infrared Raman spectroscopy

We demonstrate the use of Raman spectroscopy to measure the concentration of many important constituents (analytes) in serum and whole blood samples at physiological concentration in vitro across a multipatient data set. A near-infrared (830-nm) diode laser generates Raman spectra that contain superpositions of Raman signals from different analytes. Calibrations for glucose, cholesterol, urea, and other analytes are developed by use of partial least-squares cross validation. We predict six analytes in serum with significant accuracy in a 66-patient data set, using 60-s spectra. The calibrations are shown to be fairly robust against system drift over the span of seven weeks. In whole blood, a preliminary analysis yields accurate predictions of some of the same analytes and also hematocrit. The results hold promise for potential medical applications.     

Glucose sensing using near-infrared surface-enhanced Raman spectroscopy: gold surfaces, 10-day stability, and improved accuracy

This research presents the achievement of significant milestones toward the development of a minimally invasive, continuously monitoring, glucose-sensing platform based on the optical quantitation of glucose in interstitial fluid. We expand our initial successes in the measurement of glucose by surface-enhanced Raman scattering (SERS), demonstrating substantial improvements not only in the quality and optical properties of the substrate system itself but also in the robustness of the measurement methodology and the amenability of the technique to compact, diode laser-based instrumentation. Herein, we compare the long-term stability of gold to silver film over nanosphere (AuFON, AgFON) substrates functionalized with a partitioning self-assembled monolayer (SAM) using both electrochemical and SERS measurements. AuFONs were found to be stable for a period of at least 11 days. The switch to AuFONs not only provides a more stable surface for SAM formation but also yields better chemometric results, with improved calibration and validation over a range of 0.5-44 mM (10-800 mg/dL). Measured values for glucose concentrations in phosphate-buffered saline (pH approximately 7.4) based on 160 independent SERS measurements on AuFONs have a root-mean-square error of prediction of 2.7 mM (49.5 mg/dL), with 91% of the values falling within an extended A-B range on an expanded Clarke error grid. Furthermore, AuFONs exhibit surface plasmon resonances at longer wavelengths than similar AgFONs, which make them more efficient for SERS at near-infrared wavelengths, enabling the use of low-power diode lasers in future devices.     

Rapid, noninvasive concentration measurements of aqueous biological analytes by near-infrared Raman spectroscopy

Accurate concentration measurements of glucose, lactic acid, and creatinine in saline solution have beena chieved with near-IR Raman spectroscopy and a partial least-squares analysis. The Raman spectra were acquired remotely through optical fibers. A root-mean-squared prediction error of 1.2 mM for glucose concentration was achieved in 100 s. Concentrations of other analytes were predicted with similar accuracy.     

Ultrafast semiconductor spectroscopy using terahertz electromagnetic pulses

Terahertz electromagnetic pulses can serve as a new and unique tool for various types of spectroscopy. We first characterized the temporal and spatial properties of THz pulses generated from a large-aperture photoconductive antena, and then used them for the study of the ultrafast dynamics of electrons in semiconductros. We studied the dynamics of electrons generated by femtosecond optical pulses with positive and negative excess energies in GaAs and InP by observing the waveform of the emitted THz radiation. Subpicosecond intraband relaxation was observed with positive excess energies. With negative excess energies, a picosecond transition from the Urbach state to free carrier states was observed.     

Quantitative nondestructive methods for the determination of ticlopidine in tablets using reflectance near-infrared and Fourier transform Raman spectroscopy

Two different nondestructive spectroscopy methods based on near-infrared (NIR) and Fourier transform (FT) Raman spectroscopy were developed for the determination of ticlopidine-hydrochloride (TCL) in pharmaceutical formulations and the results were compared to those obtained by high-performance liquid chromatography (HPLC). An NIR assay was performed by reflectance over the 850-1700 nm region using a partial least squares (PLS) prediction model, while the absolute FT-Raman intensity of TCL's most intense vibration was used for constructing the calibration curve. For both methodologies the spectra were obtained from the as-received film-coated tablets of TCL. The two quantitative techniques were built using five "manual compressed" tablets containing different concentrations and validated by evaluating the calibration model as well as the accuracy and precision. The models were applied to commercial preparations (Ticlid). The results were compared to those obtained from the application of HPLC using the methodology described by "Sanofi Research Department" and were found to be in excellent agreement, proving that NIR, using fiber-optic probes, and FT-Raman spectroscopy can be used for the fast and reliable determination of the major component in pharmaceutical analysis.     

Structural analysis of triacylglycerols and edible oils by near-infrared Fourier transform Raman spectroscopy

Fourier transform Raman spectroscopy was employed for structural analysis of triacylglycerols and edible oils. Raman spectra sensitively reflected structural changes in oils. Even slight structural fluctuation between triacylglycerols and free fatty acids led to obvious differences in Raman bands as shown by C-O-C stretching from 800 to 1000 cm(-1) and the band at 1742 cm(-1). Structural difference in geometric isomers was easily distinguished as proved by C = C stretching at 1655 cm(-1) (cis) shifting to 1668 cm(-1) (trans) and by =C-H in-plane bending at 1266 cm(-1) in cis disappearing in the trans isomer. Raman intensity at 1266, 1302, and 1655 cm(-1) changed concomitantly with the change of double-bond content in oils. It showed that FT-Raman was capable of precisly reflecting the content of double bonds in oils. A linear correlation with high consistency between the Raman intensity ratio (v1655/v1444) and the iodine value was obtained for commercial oils. Based on the results, FT-Raman spectroscopy proved itself a simple and rapid technique for oil analysis since each measurement could be directly completed in 3 min without any sample modifications.     

Noninvasive alcohol testing using diffuse reflectance near-infrared spectroscopy

A diffuse reflectance near-infrared (NIR) spectrometer was evaluated as a noninvasive alternative to breath and blood measurements for in vivo alcohol testing. A hybrid partial least squares (PLS) calibration was constructed using a combination of in vivo and in vitro spectral data. This model was subsequently evaluated for its performance in quantifying alcohol concentrations in vivo using a prospective validation study involving subjects who did not participate in the calibration. The validation study entailed induction of alcohol excursions in ten human subjects and comparison of the noninvasive NIR alcohol measurements to blood and breath alcohol measurements. Blood and breath alcohol measurements were performed at the time of each noninvasive NIR measurement (N = 372), establishing the noninvasive NIR measurement standard error relative to blood alcohol at 4.9 mg/dL (0.0049%). Assessment of the hybrid calibration model's sensitivity and selectivity provided strong evidence that the hybrid calibration yielded measurements that were both sensitive to alcohol and independent of other absorbing analytes in human tissue.     

Waterborne pathogen detection using Raman spectroscopy

Raman spectroscopy is being evaluated as a candidate technology for waterborne pathogen detection. We have investigated the impact of key experimental and background interference parameters on the bacterial species level identification performance of Raman detection. These parameters include laser-induced photodamage threshold, composition of water matrix, and organism aging in water. The laser-induced photodamage may be minimized by operating a 532 nm continuous wave laser excitation at laser power densities below 2300 W/cm(2) for Grampositive Bacillus atrophaeus (formerly Bacillus globigii, BG) vegetative cells, 2800 W/cm(2) for BG spores, and 3500 W/cm(2) for Gram-negative E. coli (EC) organisms. In general, Bacillus spore microorganism preparations may be irradiated with higher laser power densities than the equivalent Bacillus vegetative preparations. In order to evaluate the impact of background interference and organism aging, we selected a biomaterials set comprising Gram-positive (anthrax simulants) organisms, Gram-negative (plague simulant) organisms, and proteins (toxin simulants) and constructed a Raman signature classifier that identifies at the species level. Subsequently, we evaluated the impact of tap water and storage time in water (aging) on the classifier performance when characterizing B. thuringiensis spores, BG spores, and EC cell preparations. In general, the measured Raman signatures of biological organisms exhibited minimal spectral variability with respect to the age of a resting suspension and water matrix composition. The observed signature variability did not substantially degrade discrimination performance at the genus and species levels. In addition, Raman chemical imaging spectroscopy was used to distinguish a mixture of BG spores and EC cells at the single cell level.     

Directivity enhanced Raman spectroscopy using nanoantennas

Directing the emission from optical emitters is highly desired for efficient detection and, by reciprocity, efficient excitation as well. As a scattering process, Raman benefits from directivity enhancements in both excitation and emission. Here we demonstrate directivity enhanced Raman scattering (DERS) using a nanoantenna fabricated by focused ion beam milling. The nanoantenna uses a resonant ring-reflector to shape the emitted beam and achieve DERS-this configuration is most similar to a waveguide antenna. The ring reflector boosts the measured Raman signal by a factor of 5.5 (as compared to the ground plane alone), and these findings are in quantitative agreement with comprehensive numerical simulations. The present design is nearly optimal in the sense that almost all the beam power is coupled into the numerical aperture of the microscope. Furthermore, the emission is directed out of the plane, so that this design can be used to achieve DERS using conventional Raman microscopes, which has yet to be achieved with Yagi-Uda and traveling wave antenna designs.     

Conductivity of nanoporous InP membranes investigated using terahertz spectroscopy

We have investigated the terahertz conductivity of extrinsic and photoexcited electrons in nanoporous indium phosphide (InP) at different pore densities and orientations. The form of electronic transport in the film was found to differ significantly from that for bulk InP. While photo-generated electrons showed Drude-like transport, the behaviour for extrinsic electrons deviated significantly from the Drude model. Time-resolved photoconductivity measurements found that carrier recombination was slow, with lifetimes exceeding 1?ns for all porosities and orientations. When considered together, these findings suggest that the surfaces created by the nanopores strongly alter the dynamics of both extrinsic and photoexcited electrons.     

Concentration measurements of multiple analytes in human sera by near-infrared laser Raman spectroscopy

Our primary goal in this study is to demonstrate that near-infrared Raman spectroscopy is feasible as a rapid and reagentless analytic method for clinical diagnostics. Raman spectra were collected on human sera by use of a 785-nm excitation laser and a single-stage holographic spectrometer. A partial-least-squares method was used to predict the analyte concentrations of interest. The prediction errors of total protein, albumin, triglyceride, and glucose in human sera ranged from 1.0% to 10%, which are highly acceptable for clinical diagnosis, of their mean physiological levels. For investigating the potential application of near-infrared Raman spectroscopy in screening of therapeutical drugs and substances of abuse the concentrations of acetaminophen, ethanol, and codeine in water solution were measured in the same fashion. The errors of the Raman tests for acetaminophen and ethanol are lower than their toxic levels in human serum, and the sensitivity for detection of codeine fails to reach its toxic level.     

Detection of apple juice adulteration using near-infrared transflectance spectroscopy

Near-infrared transflectance spectroscopy was used to detect adulteration of apple juice samples. A total of 150 apple samples from 19 different varieties were collected in two consecutive years from orchards throughout the main cultivation areas in Ireland. Adulterant samples at 10, 20, 30, and 40% w/w were prepared using two types of adulterants: a high fructose corn syrup (HFCS) with 45% fructose and 55% glucose, and a sugars solution (SUGARS) made with 60% fructose, 25% glucose, and 15% sucrose (the average content of these sugars in apple juice). The results show that NIR analysis can be used to predict adulteration of apple juices by added sugars with a detection limit of 9.5% for samples adulterated with HFCS, 18.5% for samples adulterated with SUGARS, and 17% for the combined (HFCS + SUGARS) adulterants. Discriminant partial least squares (PLS) regression can detect authentic apple juice with an accuracy of 86-100% and adulterant apple juice with an accuracy of 91-100% depending on the adulterant type and level of adulteration considered. This method could provide a rapid screening technique for the detection of this type of apple juice adulteration, although further work is required to demonstrate model robustness.     

Main inorganic component measurement of seawater using near-infrared spectroscopy

The potential of near-infrared (NIR) spectroscopy to measure the main inorganic components of seawater as salt-manufacturing materials was investigated. A total of 72 seawater samples collected from six locations was used, and spectra (1100-1800 nm) were acquired by a NIR spectrophotometer with a 1-mm path length. Principal component analysis (PCA), canonical correlation analysis (CCA), and partial least-squares (PLS) regression were performed based on the reference inorganic components. As a result, the principal component analysis and canonical correlation analysis showed that the near-infrared spectra could be related to the inorganic components of seawater. The partial least-squares regression analysis showed that the inorganic components (ion concentration of Cl, Na+, K+, SO4(2-), and Ca2+) could be predicted with good accuracy using NIR spectra and their second derivatives. For Cl ion and K+ ion concentrations, the accuracy was high.     

Nondestructive assessment of engineered cartilage constructs using near-infrared spectroscopy

Noninvasive assessment of engineered cartilage properties would enable better control of the developing tissue towards the desired structural and compositional endpoints through optimization of the biochemical environment in real time. The objective of this study is to assess the matrix constituents of cartilage using near-infrared spectroscopy (NIRS), a technique that permits full-depth assessment of developing engineered tissue constructs. Mid-infrared (mid-IR) and NIR data were acquired from full-thickness cartilage constructs that were grown up to 4 weeks with and without mechanical stimulation. Correlations were assessed between established mid-IR peak areas that reflect the relative amount of collagen (amide I, amide II, and 1338 cm(-1)) and proteoglycan (PG), (850 cm(-1)), and the integrated area of the NIR water absorbance at 5190 cm(-1). This analysis was performed to evaluate whether simple assessment of the NIR water absorbance could yield information about matrix development. It was found that an increase in the mid-IR PG absorbance at 850 cm(-1) correlated with the area of the NIR water peak (Spearman's rho = 0.95, p < 0.0001). In the second analysis, a partial least squares method (PLS1) was used to assess whether an extended NIR spectral range (5400-3800 cm(-1)) could be utilized to predict collagen and proteoglycan content of the constructs based on mid-IR absorbances. A subset of spectra was randomly selected as an independent prediction set in this analysis. Average of the normalized root mean square errors of prediction of first-derivative NIR spectral models were 7% for 850 cm(-1) (PG), 11% for 1338 cm(-1) (collagen), 8% for amide II (collagen), and 8% for amide I (collagen). These results demonstrate the ability of NIRS to monitor macromolecular content of cartilage constructs and is the first step towards employing NIR to assess engineered cartilage in situ.     

Temperature measurements of turbid aqueous solutions using near-infrared spectroscopy

We report a method that uses near-infrared spectroscopy and multivariate analysis to measure the temperature of turbid aqueous solutions. The measurement principle is based on the fact that the peak wavelength of the water absorption band, with its center near 1440 nm, shifts with changes in temperature. This principle was used to measure the temperatures of 1 mm thick samples of aqueous solutions containing Intralipid (2%), which are often used as optical phantoms for biological tissues due to similar scattering characteristics. Temperatures of pure water and aqueous solutions containing glucose (100 mg/ml and 200 mg/ml) were also measured for comparison. For the turbid Intralipid solutions, the absorbance spectrum varied irregularly with time due to the change in scattering characteristics. However, by making use of the difference between the absorbance at 1412 nm and the temperature-independent absorbance at 1440 nm, we obtained SEPs (standard error of prediction) of 0.3 degrees C and 0.2 degrees C by univariate linear regression and partial least squares regression, respectively. These accuracies were almost the same as those for the transparent samples (pure water and glucose solution).     

Quantifying ethanol content of beer using interpretive near-infrared spectroscopy

On the basis of absorption measurements in the near-infrared (NIR) spectral range, a new method for the quantification of the ethanol content of beer is presented. Instead of the multivariate calibration models most commonly employed in NIR spectroscopic works, we use interpretive difference spectroscopy: Two wavelengths are selected according to the assignment of the absorption bands of the main substances of content of beer in the NIR region, and the difference between the absorbances at these wavelengths is used for ethanol quantification. Absorption spectra of the dominating beer ingredients are discussed and the calibration procedure with ethanol/water mixtures is shown. Robustness against the carbohydrate content of beer samples was demonstrated by analyzing solutions of ethanol and maltose in water. Validation of the method was performed with various beer samples with an ethanol concentration range between 0.5 and 7.7 vol %. The pertinent advantage of the procedure developed in this work is the indication that the results are independent from seasonal variations of the ingredients, which is of high interest for products with natural ingredients such as beer.     

Discrimination of bacteria using surface-enhanced Raman spectroscopy

Raman spectroscopy has recently been shown to be a potentially powerful whole-organism fingerprinting technique and is attracting interest within microbial systematics for the rapid identification of bacteria and fungi. However, while the Raman effect is so weak that only approximately 1 in 10(8) incident photons are Raman scattered (so that collection times are in the order of minutes), it can be greatly enhanced (by some 10(3)-10(6)-fold) if the molecules are attached to, or microscopically close to, a suitably roughened surface, a technique known as surface-enhanced Raman scattering (SERS). In this study, SERS, employing an aggregated silver colloid substrate, was used to analyze a collection of clinical bacterial isolates associated with urinary tract infections. While each spectrum took 10 s to collect, to acquire reproducible data, 50 spectra were collected making the spectral acquisition times per bacterium approximately 8 min. The multivariate statistical techniques of discriminant function analysis (DFA) and hierarchical cluster analysis (HCA) were applied in order to group these organisms based on their spectral fingerprints. The resultant ordination plots and dendrograms showed correct groupings for these organisms, including discrimination to strain level for a sample group of Escherichia coli, which was validated by projection of test spectra into DFA and HCA space. We believe this to be the first report showing bacterial discrimination using SERS.     

Studying bacterial metabolic states using Raman spectroscopy

Natural metabolic variability expected during characteristic growth phases in batch cultures of Escherichia coli and Staphylococcus epidermidis were studied by Raman spectroscopy. Spectral changes induced by metabolic changes found in the growth phases (i.e., lag, exponential, stationary, and decay) were identified. Maximum intensity of bands assigned to DNA and RNA bases are seen at the beginning of the exponential phase, when cells are metabolically active, and minimum intensities are seen when cells are decaying. High agreement in spectral variation due to growth phases was seen for all the trials that were performed, four growth cycles for E. coli and two for S. epidermidis. Batch cultures were monitored by standard plate counts to identify all growth phases, including decay. Spectral data were analyzed by principal component analysis (PCA) and discriminant analysis to identify similarities and differences and to estimate a classification performance based on growth phases. For the species evaluated, spectra during decay are grouped closer to each other and separated from lag, exponential, and stationary cells. These results suggest that Raman spectroscopy can be used to study metabolic states in bacteria and in particular cell viability.     

Raman and near-infrared spectroscopy for quantification of fat composition in a complex food model system

Raman and near-infrared (NIR) spectroscopy have been evaluated for determining fatty acid composition and contents of main constituents in a complex food model system. A model system consisting of 70 different mixtures of protein, water, and oil blends was developed in order to create a rough chemical imitation of typical fish and meat samples, showing variation both in fatty acid composition and in contents of main constituents. The model samples as well as the pure oil mixtures were measured using Raman and NIR techniques. Partial least squares regression was utilized for prediction, and fatty acid features were expressed in terms of the iodine value and as contents of saturated, monounsaturated, and polyunsaturated fatty acids. Raman spectroscopy provided the best results for predicting iodine values of the model samples, giving validated estimation errors accounting for 2.8% of the total iodine value range. Both techniques provided good results for predicting the content of saturated, monounsaturated, and polyunsaturated fatty acids in the model samples, yielding validated estimation errors in the range of 2.4-6.1% of the total range of fatty acid content. Prediction results for determining fatty acid features of the pure oil mixtures were similar for the two techniques. NIR was clearly the best technique for modeling content of main constituents in the model samples.