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We report the manipulation of nitrogen vacancy (NV) spins in diamond when nearby ferrimagnetic insulator, yttrium iron garnet, is driven into precession. The change in NV spin polarization, as measured by changes in photoluminescence, is comparable in magnitude to that from conventional optically detected magnetic resonance, but relies on a distinct mechanism as it occurs at a microwave frequency far removed from the magnetic resonance frequency of the NV spin. This observation presents a new approach to transferring ferromagnetic spin information into a paramagnet and then transducing the response into a robust optical signal. It also opens new avenues for studying ferromagnetism and spin transport at the nanoscale., Comment: 3 figures

We present an angular-scattering optical method that is capable of measuring the mean size of scatterers in static ensembles within a field of view less than 20 μm in diameter. Using interferometry, the method overcomes the inability of intensity-based models to tolerate the large speckle grains associated with such small illumination areas. By first estimating each scatterer’s location, the method can model between-scatterer interference as well as traditional single-particle Mie scattering. Direct angular-domain measurements provide finer angular resolution than digitally transformed image-plane recordings. This increases sensitivity to size-dependent scattering features, enabling more robust size estimates. The sensitivity of these angular-scattering measurements to various sizes of polystyrene beads is demonstrated. Interferometry also allows recovery of the full complex scattered field, including a size-dependent phase profile in the angular-scattering pattern.

Lasers are important tools in many diabetes-related applications, both diagnostic and therapeutic. Despite its wide range of uses, the laser derives all of its advantages over more conventional light sources from a few basic principles. A brief introduction to the fundamental properties of lasers emphasizes these points and suggests ways in which they can be exploited in experiments. Short descriptions of particular laser-based methods for monitoring glucose and related molecules provide introductions to research articles on these subjects.

We present a new method of linear multivariate calibration that can generate better prediction results than those obtained by partial least squares (PLS). This is accomplished by incorporating the spectrum of the desired species into the calibration procedure. The method combines the advantages of different standard methods and is therefore called hybrid linear analysis (HLA). In side-by-side tests using both simulated and experimental data, HLA produced lower prediction errors than PLS in all instances. We recommend HLA over PLS in situations where the spectrum of the desired species is available.

We present an analytical formula that estimates the uncertainty in concentrations predicted by linear multivariate calibration, particularly partial least-squares (PLS). We emphasize the analysis of spectroscopic data. The derivation addresses the important limit in which calibration error is negligible in comparison to noise in the prediction spectra. The formula is expressed in terms of standard PLS calibration parameters and the amplitude of spectral noise; it is therefore straightforward to evaluate. To test the formula, we performed PLS analysis upon simulated spectra and upon experimental Raman spectra of dissolved biological analytes in water. In each instance, the root-mean-squared error of prediction was compared to the estimate from the formula. Accurate uncertainty estimates were obtained in cases where calibration noise was lower than prediction noise, and surprisingly good estimates were obtained even when the noise levels were equal. By comparing measured and estimated uncertainties, we assessed the robustness of each PLS calibration model. The scaling of prediction uncertainty with the spectral signal-to-noise ratio is also discussed.

Spintronics use the electron spin as a state variable for information processing and storage. This requires manipulation of spin ensembles for data encoding, and spin transport for information transfer. Because of the central importance of lifetime for understanding and controlling spins, mechanisms that determine this lifetime in bulk systems have been extensively studied. However, a clear understanding of few-spin systems remains challenging. Here, we report spatially resolved magnetic resonance studies of electron spin ensembles confined to a 'spin nanowire' formed by nitrogen ion implantation in diamond. We measure the spin lifetime of the ensemble--that is, its spin autocorrelation time--by monitoring the statistical fluctuations of its net moment, which is in thermal equilibrium and has no imposed polarization gradient. We find that the lifetime of the ensemble is dominated by spin transport from the ensemble into the adjacent spin reservoir that is provided by the remainder of the nanowire. This is in striking contrast to conventional spin-lattice relaxation measurements of isolated spin ensembles. Electron spin resonance spectroscopy performed on nanoscale spin ensembles by means of a novel spin manipulation protocol corroborates spin transport in strong field gradients. Our experiments, supported by microscopic Monte Carlo modelling, provide a unique insight into the intrinsic dynamics of pure spin currents needed for nanoscale devices that seek to control spins.

Progress in spintronics has been aided by characterization tools tailored to certain archetypical materials. New device structures and materials will require characterization tools that are material independent, provide sufficient resolution to image locally-varying spin properties and enable subsurface imaging. Here we report the demonstration of a novel spin-microscopy tool based on the variation of a global spin-precession signal in response to the localized magnetic field of a scanned probe. We map the local spin density in optically pumped GaAs from this spatially-averaged signal with a resolution of 5.5 microns. This methodology is also applicable to other spin properties and its resolution can be improved. It can extend spin microscopy to device structures not accessible by other techniques, such as buried interfaces and non-optically active materials, due to the universal nature of magnetic interactions between the spins and the probe., Comment: Supplementary information added at the end of the main article. Main article: 6 pages 5 figures, Supplementary: 9 pages, 6 figures. The original files are PDFLatex

Ferromagnetic resonance (FMR) spin pumping is a rapidly growing field which has demonstrated promising results in a variety of material systems. This technique utilizes the resonant precession of magnetization in a ferromagnet to inject spin into an adjacent non-magnetic material. Spin pumping into graphene is attractive on account of its exceptional spin transport properties. This article reports on FMR characterization of cobalt grown on CVD graphene and examines the validity of linewidth broadening as an indicator of spin pumping. In comparison to cobalt samples without graphene, direct contact cobalt-on-graphene exhibits increased FMR linewidth--an often used signature of spin pumping. Similar results are obtained in Co/MgO/graphene structures, where a 1nm MgO layer acts as a tunnel barrier. However, SQUID, MFM, and Kerr microscopy measurements demonstrate increased magnetic disorder in cobalt grown on graphene, perhaps due to changes in the growth process and an increase in defects. This magnetic disorder may account for the observed linewidth enhancement due to effects such as two-magnon scattering or mosaicity. As such, it is not possible to conclude successful spin injection into graphene from FMR linewidth measurements alone.

Clinical prediction of bone fracture risk primarily relies on measures of bone mineral density (BMD). BMD is strongly correlated with bone strength, but strength is independent of fracture toughness, which refers to the bone's resistance to crack initiation and propagation. In that sense, fracture toughness is more relevant to assessing fragility-related fracture risk, independent of trauma. We hypothesized that bone biochemistry, determined by Raman spectroscopy, predicts bone fracture toughness better than BMD. This hypothesis was tested in tumor necrosis factor-transgenic mice (TNF-tg), which develop inflammatory-erosive arthritis and osteoporosis. The left femurs of TNF-tg and wild type (WT) littermates were measured with Raman spectroscopy and micro-computed tomography. Fracture toughness was assessed by cutting a sharp notch into the anterior surface of the femoral mid-diaphysis and propagating the crack under 3 point bending. Femoral fracture toughness of TNF-tg mice was significantly reduced compared to WT controls (p=0.04). A Raman spectrum-based prediction model of fracture toughness was generated by partial least squares regression (PLSR). Raman spectrum PLSR analysis produced strong predictions of fracture toughness, while BMD was not significantly correlated and produced very weak predictions. Raman spectral components associated with mineralization quality and bone collagen were strongly leveraged in predicting fracture toughness, reiterating the limitations of mineralization density alone.

The observation of surface-enhanced Raman scatterings (SERS) from CO2 molecules dissolved in aqueous solutions of silver and gold colloids measured with 850 nm near-IR excitation is reported. Different types of surface enhancement and surface-enhanced Raman spectra were observed. The SERS spectrum of CO2 on colloidal gold is in good agreement with the spectrum of CO2 dissolved in water. Two different types of SERS spectra were found for CO2 on colloidal silver. They can be assigned to physisorbed and/or weakly chemisorbed CO2 molecules and to strongly bonded CO2 - negatively charged surface radicals, respectively. The enhancement factor for the stretching mode of carbon dioxide is estimated to be of the order of 102−104, depending on the kinds of metal and types of adsorption, which demonstrates that SERS on colloidal silver or gold particles in solution offers possibilities for detecting CO2 dissolved in liquids at low concentrations.

Near-infrared Raman spectra of several gases dissolved in an aqueous medium have been acquired and analyzed for the first time. Spectra of dissolved and gaseous CO2, SO2, N2O, dimethyl ether, and O2 are presented and compared. Raman-forbidden bands in the spectrum of gaseous dimethyl ether are observed in the dissolved spectrum; this result can be explained by relaxed selection rules due to lowered symmetry. Raman scattering enhancements in the dissolved phase are measured and shown to compare well with a theoretical prediction accounting for internal field enhancements in water. Dissolved CO2 is measured quantitatively at concentrations from 0 to 250 Torr with the use of the method of partial least-squares, with an average prediction error of 12 Torr.

Abstract A new method of mapping multiple species of oral bacteria in intact biofilms has been developed, using the optical technique of confocal Raman microscopy. A species classification algorithm, developed on dried biofilms, was used to analyze spectra of hydrated biofilms containing two microbial species central to dental health: Streptococcus sanguinis and Streptococcus mutans. The algorithm transferred successfully to the hydrated environment, correctly identifying the species of origin of single-species biofilms. We then used the algorithm successfully both to detect the presence of two species in mixed biofilms and to create spatial maps within these biofilms.

Although glucocorticoids are among the most frequently prescribed anti-inflammatory agents used in the treatment of rheumatoid arthritis, extended exposure to this steroid hormone is the leading cause of iatrogenic osteoporosis. Recently, Raman spectroscopy has been utilized to exploit biochemical differences between osteoporotic and normal bones in order to predict fracture risk. In this presentation, we report the results of ongoing research in our laboratory towards the clinical translation of this technique. We will discuss strategies for the transcutaneous acquisition of spectra from the tibiae of mice that are of sufficient quality to generate accurate predictions of fracture risk.

Using integrated Raman and angular scattering microscopy (IRAM), we follow the response of EMT6 cancer cells to photodynamic therapy (PDT) treatment. The study combines two non-labelling light scattering techniques to extract chemical information and organelle sizes from single cells. Each cell is measured repeatedly over several hours to follow changes in these parameters as the cell responds to the PDT treatment. An automated algorithm identifies which parameters are changing in time. Size parameters extracted from angular scattering measurements show a decrease in the size of 1-micron-diameter scatterers in treated cells. Treated cells also exhibit trends in several Raman peaks, denoting changes in chemical concentrations of proteins, nucleic acids, and lipids. Each of these parameters - acquired from both measurement modalities - can be monitored on a cell-by-cell basis. The ability to track these chemical and structural changes over time allows access to greater knowledge of biological processes.

Near-infrared spectroscopy (NIRS) sensing of cerebral hemodynamics can be made more brain-specific by regressing against superficially-sensitive channels. Different distances and single channels versus global averages are discussed.

Near-infrared spectroscopy is a non-invasive diffuse optical-imaging technique for estimating the metabolic demand in local (1 cm) regions of cortex. Activations in visual cortex of human adults and infants are consistent with known projections from the two hemi-fields.

Although glucocorticoids are frequently prescribed for the symptomatic management of inflammatory disorders such as rheumatoid arthritis, extended glucocorticoid exposure is the leading cause of physician-induced osteoporosis and leaves patients at a high risk of fracture. To study the biochemical effects of glucocorticoid exposure and how they might affect biomechanical properties of the bone, Raman spectra were acquired from ex vivo tibiae of glucocorticoid- and placebo-treated wild-type mice and a transgenic mouse model of rheumatoid arthritis. Statistically significant spectral differences were observed due to both treatment regimen and mouse genotype. These differences are attributed to changes in the overall bone mineral composition, as well as the degree of phosphate mineralization in tibial cortical bone. In addition, partial least squares regression was used to generate a Raman-based prediction of each tibia's biomechanical strength as quantified by a torsion test. The Raman-based predictions were as accurate as those produced by microcomputed tomography derived parameters, and more accurate than the clinically-used parameter of bone mineral density. These results suggest that Raman spectroscopy could be a valuable tool for monitoring bone biochemistry in studies of bone diseases such as osteoporosis, including tests of drugs being developed to combat these diseases.

Glucocorticoids are frequently used to treat inflammatory disorders such as rheumatoid arthritis. Unfortunately, extended exposure to this steroid is the leading cause of physician-induced osteoporosis, leaving patients susceptible to fractures at rates of 30-50%. In this presentation, we report correlations between Raman spectra and biomechanical strength tests on bones of glucocorticoid- and placebo- treated mice. Both wild-type mice and a transgenic model of rheumatoid arthritis have been studied. A two-way ANOVA model reveals statistically significant spectral differences as influenced by glucocorticoid treatment and mouse type.

Implemented through a confocal microscope, Raman spectroscopy has been used to distinguish between biofilm samples of two common oral bacteria species, Streptococcus sanguinis and mutans, which are associated with healthy and cariogenic plaque, respectively. Biofilms of these species are studied as a model of dental plaque. A prediction model has been calibrated and validated using pure biofilms. This model has been used to identify the species of transferred and dehydrated samples (much like a plaque scraping) as well as hydrated biofilms in situ. Preliminary results of confocal Raman mapping of species in an intact two-species biofilm will be shown.

We describe a compound parabolic concentrator (CPC)-based probe for enhanced signal collection in the spectroscopy of biological tissues. Theoretical considerations governing signal enhancement compared with conventional collection methods are given. A ray-tracing program was used to analyze the throughput of CPC's with shape deviations and surface imperfections. A modified CPC shape with 99% throughput was discovered. A 4.4-mm-long CPC was manufactured and incorporated into an optical fiber-based near-infrared Raman spectrometer system. For human tissue samples, light collection was enhanced by a factor of 7 compared with collection with 0.29-NA optical fibers.

Accurate concentration measurements of glucose, lactic acid, and creatinine in saline solution have been achieved 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.

Functional near infrared spectroscopy (fNIRS) is a portable monitor of cerebral hemodynamics with wide clinical potential. However, in fNIRS, the vascular signal from the brain is often obscured by vascular signals present in the scalp and skull. In this paper, we evaluate two methods for improving in vivo data from adult human subjects through the use of high-density diffuse optical tomography (DOT). First, we test whether we can extend superficial regression methods (which utilize the multiple source–detector pair separations) from sparse optode arrays to application with DOT imaging arrays. In order to accomplish this goal, we modify the method to remove physiological artifacts from deeper sampling channels using an average of shallow measurements. Second, DOT provides three-dimensional image reconstructions and should explicitly separate different tissue layers. We test whether DOT's depth-sectioning can completely remove superficial physiological artifacts. Herein, we assess improvements in signal quality and reproducibility due to these methods using a well-characterized visual paradigm and our high-density DOT system. Both approaches remove noise from the data, resulting in cleaner imaging and more consistent hemodynamic responses. Additionally, the two methods act synergistically, with greater improvements when the approaches are used together.

A Raman spectroscopy system has been constructed to study the chemical perturbations to cortical bone associated with steroid induced osteoporosis. Transcutaneous measurements of bone are also discussed.

Integrated Raman- and Angular-scattering Microscopy (IRAM) uses chemical and morphological data to differentiate between activated and resting immune cells. IRAM can now monitor these changes over time to study the immune cell activation process.

Confocal Raman microscopy has been used to distinguish between biofilms of oral bacteria species Streptococcus sanguis and mutans. This capability has been applied to the study of mixed biofilms as a model for dental plaque.

Blood and urine are frequently analyzed for their chemical content. Raman spectroscopy, with its high specificity, can provide chemical information in a non-contact and potentially non-invasive manner. In this chapter, key experimental and analytical techniques for converting Raman spectra into quantitative chemical concentration measurements are presented, along with a survey of the current status of the field.

A multidetector, continuous wave, near-infrared spectroscopy (NIRS) system is developed to examine whether the hemodynamics of the scalp and brain in adults contain significant layer-like hemodynamic trends. NIRS measurements are made using contrasting geometries, one with four detectors equidistant from a source 33 mm away, and one with detectors collinear with the source (5 to 33 mm away). When NIRS time series are acquired over the prefrontal cortex from resting adults using both geometries, variations among the time series are consistent with a substantially homogeneous two-layer model (p

A technique for measuring broadband near-infrared absorption spectra of turbid media that uses a combination of frequency-domain (FD) and steady-state (SS) reflectance methods is presented. Most of the wavelength coverage is provided by a white-light SS measurement, whereas the FD data are acquired at a few selected wavelengths. Coefficients of absorption (μa) and reduced scattering (μ‘s) derived from the FD data are used to calibrate the intensity of the SS measurements and to estimate μ‘s at all wavelengths in the spectral window of interest. After these steps are performed, one can determine ma by comparing the SS reflectance values with the predictions of diffusion theory, wavelength by wavelength. Absorption spectra of a turbid phantom and of human breast tissue in vivo, derived with the combined SSFD technique, agree well with expected reference values. All measurements can be performed at a single source-detector separation distance, reducing the variations in sampling volume that exist in multidistance methods. The technique uses relatively inexpensive light sources and detectors and is easily implemented on an existing multiwavelength FD system. © 2000 Optical Society of America.

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.

A microscope system has been constructed that allows simultaneous acquisition of Raman scattering spectra and elastic scattering Fourier-plane data. The Raman scattering channel reports on chemical composition of the microscopic sample while the elastic scattering channel reports on morphological information about the sample. The system has been validated by acquiring data from single polystyrene beads and analyzing the elastic scattering signal using Generalized Lorenz-Mie Theory while comparing the Raman scattering signature to other polystyrene spectra from the literature. Monocytes and neutrophils, two immune cell types, have also been studied and show clear chemical and morphological differences between cell types.

Raman spectroscopy studies a target chemically, while angularly-resolved elastic light scattering probes morphology. We have combined these modalities on a microscopic platform. The optical system and data from beads and immune cells are discussed.

Angularly-resolved elastic scattering and spectrally-resolved Raman scattering can be recorded simultaneously from a single cell. Using the resulting morphological and chemical information, one can classify individual cells or monitor one cell's response to a stimulus.

Confocal Raman microscopy has been used to differentiate the spectra from biofilms of oral bacterial species Streptococcus sanguis and mutans. Improvements in processing algorithms allow this study to be performed using glass as a substrate.

The ability to quantify uncertainty in information extracted from spectroscopic measurements is important in numerous fields. The traditional approach of repetitive measurements may be imprac- tical or impossible in some measurements scenarios, while chi- squared analysis does not provide insight into the sources of uncer- tainty. As such, a need exists for analytical expressions for estimating uncertainty and, by extension, minimum detectable concentrations or diagnostic parameters, that can be applied to a single noisy measure- ment. This work builds on established concepts from estimation theory, such as the Cramer-Rao lower bound on estimator covariance, to present an analytical formula for estimating uncertainty expressed as a simple function of measurement noise, signal strength, and spec- tral overlap. This formalism can be used to evaluate and improve instrument performance, particularly important for rapid-acquisition biomedical spectroscopy systems. We demonstrate the experimental utility of this expression in assessing concentration uncertainties from spectral measurements of aqueous solutions and diagnostic parameter uncertainties extracted from spectral measurements of human artery tissue. The measured uncertainty, calculated from many independent measurements, is found to be in good agreement with the analytical formula applied to a single spectrum. These results are intended to encourage the widespread use of uncertainty analysis in the biomedi- cal optics community. © 2007 Society of Photo-Optical Instrumentation Engineers. DOI: 10.1117/1.2815692

Near-infrared Raman spectroscopy has been used for species identification of pure microbial specimens for more than a decade. More recently, this optical method has been extended to the analysis of specimens containing multiple species. In this report, we demonstrate rapid, reagent-free quantitative analysis of a simplified model of oral plaque containing three oral bacteria species, S. mutans, S. sanguis, and S. gordonii, using near-infrared Raman spectroscopy. Raman spectra were acquired from bacterial mixtures in 200 seconds. A prediction model was calibrated by the partial least squares method and validated by additional samples. On a scale from 0 to 1, relative fractions of each species could be predicted with a root mean square error of 0.07. These results suggest that near-infrared Raman spectroscopy is potentially useful in quantification of microbial mixtures in general and oral plaques in particular.

Raman spectra were obtained from single mouse tumor cells before and after treatment with photodynamic therapy. We are presently investigating pure chemicals to illuminate differences observed in the spectra of treated and untreated cells.

Near-infrared monitoring of cerebral hemodynamics is hampered by biological noise. We propose noise reduction via a two-detector scheme and present measurements characterizing relevant heterogeneit ...

We proposed a method to isolate cerebral NIRS signatures using measurements at two source-detector separations. To examine this method's applicability on human subjects, a series of different activation protocols are monitored via specialized NIRS probes.

This PDF file contains the editorial “Infrared and Raman Spectroscopy” for JBO Vol. 10 Issue 03

We propose a method to isolate absorption trends confined to the lower layer of a two-layer turbid medium, as is desired in near-infrared spectroscopy (NIRS) of cerebral hemodynamics. Several two-layer Monte Carlo simulations of NIRS time series were generated using a physiologically relevant range of optical properties and varying the absorption coefficients due to bottom-layer, top-layer, and/or global fluctuations. Initial results showed that by measuring absorption trends at two source-detector separations and performing a least-squares fit of one to the other, processed signals strongly resemble the simulated bottom-layer absorption properties. Through this approach, it was demonstrated that fitting coefficients can be estimated within less than +/- 2% of the ideal value without any a priori knowledge of the optical properties present in the model. An analytical approximation for the least-squares coefficient provides physical insight into the nature of errors and suggests ways to reduce them.

In a two-layer diffusing medium, polarized light directly backscattering off the superficial layer will partially retain its sense of polarization, whereas deeper-probing light will be increasingly depolarized by diffusion. This effect has been studied in both elastic scattering and fluorescence contexts. We apply this method to Raman scattering in two two-layer models with a highly diffusing lower layer of glucose powder and an upper layer of either clear plastic or chicken skin. We employ detection of orthogonal polarization states to generate a Raman spectrum of only the superficial layer by combining the orthogonal signals.

In biomedical optics, the specimens usually have a "Goldilocks" quality: some structures are much larger than an optical wavelength, some are much smaller, and some are just about the same size. Consequently, biological absorption, emission, and scattering properties can have strong wavelength and angular dependences. This tutorial will explain the nature of the dependences and survey some of the ways they are exploited for biomedical purposes.Full-text article is not available.

We investigated near-infrared Raman spectra of two kinds of oral streptococci, S. mutans and S. sanguis, at different growth stages by using principal component analysis and logistic regression Our results indicate species information and growth phase information can be extracted separately from different spectral regions.

Near-infrared Stokes spectra from biological samples were acquired using mode-locked Ti:sapphire excitation and a novel intensifier-coupled CCD with 200-psec time gating. The fluorescence exhibits nsec decay rates, suggesting that the primary fluorophore is not iron. Potential enhancement factors for time-gated suppression of fluorescence from Raman spectra can be calculated.

Teflon AF® tubing has been used as a liquid-core-optical-fiber(LCOF) to enhance the strength of Raman signals collected from urine samples. Data were collected from LCOF and traditional cuvette geometries. Creatinine and ethanol predictions in urine samples have been made using chemometric analysis. The improve in signal-to-noise-ratio(S/N) leads to better root-mean-square-error-prediction(RMSEP).

We propose a method to isolate cerebral NIRS signatures from superficial fluctuations using measurements at two source-detector separations. Two-layer Monte-Carlo simulations were used as a model, varying the absorption of each layer. Initial results show processed signals strongly resemble the simulated bottom layer absorption properties.

Spectroscopic methods of urinalysis offer several advantages over chemical methods, including less sample contact and higher information content. In particular, urine creatinine has been the subject of several spectroscopic studies. We report the first use of Raman spectroscopy to measure creatinine concentrations in unaltered urine samples from a multipatient population. Using near-infrared excitation and a hybrid linear analysis calibration method, a root mean squared error of cross-validation (RMSECV) of 4.9 mg/dL was obtained. The error in the reference chemical method was 1.1 mg/dL. This result shows that the Raman spectroscopy can measure creatinine at clinical levels even in the presence of patient-to-patient variations. Because most assays in urine require creatinine concentration in order to correct for fluctuations in water content, measurement of creatinine is the first step towards more extensive Raman-based urinalysis.

Raman spectroscopy has been employed to measure the varying concentrations of two oral bacteria in simple mixtures. Evaporated droplets of centrifuged mixtures of Streptococcus sanguis and Streptococcus mutans were analyzed via Raman microspectroscopy. The concentration of s. sanguis was determined based upon the measured Raman spectrum, using partial least squares cross-validation, with an r2 value of 0.98.

Mixtures of the two most prevalent bacteria found in oral plaques were prepared and analyzed under a Raman microscope. Relative concentrations of the two bacteria were determined with an accuracy better than that of standard lab-bench methods. Extensions to the analysis of fresh oral plaques are envisioned.

In biomedical Raman spectroscopy, strong autofluorescence from the sample usually confounds the detection of weak Raman bands. We have been investigating a computer-conrolled wavelength-shifting scheme to reduce the contribution of autofluorescence in a convenient manner.