Transmission infrared spectroscopy of whole blood--complications for quantitative analysis from leucocyte adhesion during continuous monitoring.

Infrared spectroscopy has been applied to analyse glucose and cellular components in whole blood with the aim of developing an online clinical diagnostic and monitoring modality. Leucocyte adsorption onto the CaF(2) windows was observed over a period of several hours under continuous blood flow using a transmission cell of 30 mum path length. This build-up of cellular material on the windows is responsible for diminishing the sample path length under the flow conditions chosen. The adsorption dynamics have been characterised and their impact on glucose monitoring is reported. For short-term monitoring (<2 hours) a standard error of prediction of 11 mg/dL with human citrated blood samples from three different subjects was achieved. Furthermore, the leucocyte build-up was also reported for porcine EDTA blood monitoring. Consequences and testing opportunities with regard to the first stages in the immune cell reaction to the exposure of body-foreign materials to anticoagulated whole blood are discussed.

Bedside monitoring of subcutaneous interstitial glucose in healthy individuals using microdialysis and infrared spectrometry.

An IR-spectroscopy-based bedside device, coupled to a subcutaneously implanted microdialysis probe, is developed for quasicontinuous glucose monitoring with intermittent readouts at 10-min intervals, avoiding any sensor recalibration under long-term operation. The simultaneous estimation of the microdialysis recovery rate is possible using an acetate containing perfusate and determining its losses across the dialysis membrane. Measurements are carried out on four subjects, with experiments lasting either 8 or 28 h, respectively. Using the spectral interval data either from 1180 to 950 or 1560 to 1000 cm(-1), standard errors of prediction (SEPs) between 0.13 and 0.28 mM are achieved using multivariate calibration with partial least-squares (PLS) or classical least-squares (CLS) calibration models, respectively. The transfer of a PLS calibration model using the spectral and reference concentration data of the dialysates from the three 8-h-long experiments to a 28-h monitoring episode with another healthy subject is tested. Including microdialysis recovery for the determination of the interstitial glucose concentrations, an SEP of 0.24 mM is obtained versus whole blood glucose values. The option to determine other metabolites such as urea or lactate offers the possibility to develop a calibration- and reagent-free point-of-care analyzer.

Infrared transmission spectrometry for the determination of urea in microliter sample volumes of blood plasma dialysates.

Application of mid-infrared spectroscopy for the determination of urea in blood plasma dialysates of microliter sample volumes using a transmission microcell was investigated. Infrared spectra of the dialysates of plasma samples collected from 75 different patients using CMA 60 microdialysis catheters were evaluated with multivariate partial least squares regression. Using the absorbance spectral data from 1520-1420 cm(-1) and 1220-1120 cm(-1), a minimum standard error of prediction (SEP) of 0.88 mg/dL (0.14 mM) was achieved with spectral variable selection. Our findings suggest the feasibility of developing a mid-infrared sensor in combination with micro-fluidics for on-line monitoring of urea in patients undergoing dialysis treatment.

Spectral variable selection for partial least squares calibration applied to authentication and quantification of extra virgin olive oils using Fourier transform Raman spectroscopy.

The limits of quantitative multivariate assays for the analysis of extra virgin olive oil samples from various Greek sites adulterated by sunflower oil have been evaluated based on their Fourier transform (FT) Raman spectra. Different strategies for wavelength selection were tested for calculating optimal partial least squares (PLS) models. Compared to the full spectrum methods previously applied, the optimum standard error of prediction (SEP) for the sunflower oil concentrations in spiked olive oil samples could be significantly reduced. One efficient approach (PMMS, pair-wise minima and maxima selection) used a special variable selection strategy based on a pair-wise consideration of significant respective minima and maxima of PLS regression vectors, calculated for broad spectral intervals and a low number of PLS factors. PMMS provided robust calibration models with a small number of variables. On the other hand, the Tabu search strategy recently published (search process guided by restrictions leading to Tabu list) achieved lower SEP values but at the cost of extensive computing time when searching for a global minimum and less robust calibration models. Robustness was tested by using packages of ten and twenty randomly selected samples within cross-validation for calculating independent prediction values. The best SEP values for a one year's harvest with a total number of 66 Cretian samples were obtained by such spectral variable optimized PLS calibration models using leave-20-out cross-validation (values between 0.5 and 0.7% by weight). For the more complex population of olive oil samples from all over Greece (total number of 92 samples), results were between 0.7 and 0.9% by weight with a cross-validation sample package size of 20. Notably, the calibration method with Tabu variable selection has been shown to be a valid chemometric approach by which a single model can be applied with a low SEP of 1.4% for olive oil samples across three different harvest years.

Nanoliter serum sample analysis by mid-infrared spectroscopy for minimally invasive blood-glucose monitoring.

The aim of this study was to demonstrate that mid-infrared spectroscopy is able to quantify glucose in a serum matrix with sample volumes well below 1 muL. For this, we applied mid-infrared attenuated total reflectance (ATR) or transmission-based spectroscopic methods to glucose quantification in microsamples of dry-film sera, either undiluted or diluted 10 times in distilled water. The sample series spanned physiological glucose concentrations between 50 and 600 mg/dL and volumes of 80, 8, and 1 nL. Calibration was carried out using multivariate partial least-squares (PLS) modeling with spectral data between 1180 and 940 cm(-1). Best performance was achieved in the ATR experiments. For raw ATR spectra, the optimum standard error of prediction (SEP) of 13.3 mg/dL was obtained for the 8 nL sample series with subsequent 10-fold dilution. With respect to the coefficient of variation of the glucose assay, CV(pred), we obtained a value of 3% for the 80 nL volume samples with spectral preprocessing using matrix protein absorption bands as an internal standard, 4% for the 8 nL samples, and 6% for the 1 nL samples with raw data. Spectral standardization resulted in significant improvement, especially for the 80 nL volume sample series. By contrast, the accuracy of the glucose assay for the 1 nL sample volume series could not be improved either by internal standardization or by considering the dry film areas for normalization, which we attribute to varying topographies of the dry films.

Glucose quantification in dried-down nanoliter samples using mid-infrared attenuated total reflection spectroscopy.

The aim of this study was to determine the feasibility of minimally invasive glucose concentration measurement of a body fluid within the physiologically important range below 100 nL with a number of samples such as interstitial fluid, plasma, or whole blood using mid-infrared spectroscopy, but starting with preliminary measurements on samples of simple aqueous glucose solutions. The Fourier transform infrared spectrometer was equipped with a Golden Gate single reflection diamond attenuated total reflection (ATR) accessory and a room-temperature pyroelectric detector. As the necessary detection limits can be achieved only for dried samples within the spectrometric conditions realized by a commercial instrument, the work focused on the optimization of such ATR measurements. We achieved quantification of samples with volumes as low as 7 nL between 10 and 600 mg/dL. The standard error of prediction (SEP) for the concentration range 10-100 mg/dL is 3.2 mg/dL with full interval data between 1180 and 940 cm(-1). The performance of the prediction is given by a coefficient of variation of prediction (CV(pred) ) of 6.2%. When all samples within the whole concentration range are included, the SEP increases to 20.2 mg/dL, and hence the CV(pred) to 10.6% due to a nonlinear signal dependence on glucose concentration. A detection limit for glucose of 0.7 ng with a signal-to-noise ratio of 10 was obtained.