Julia Kuligowski

Analytical potential of mid-infrared detection in capillary electrophoresis and liquid chromatography: a review.

Literature published in the last decade concerning the use of mid-infrared spectrometry as a detection system in separation techniques employing a liquid mobile phase is reviewed. In addition to the continued use of isocratic liquid chromatographic (LC) techniques, advances in chemometric data evaluation techniques now allow the use of gradient techniques on a routine basis, thus significantly broadening the range of possible applications of LC-IR. The general trend towards miniaturized separation systems was also followed for mid-IR detection where two key developments are of special importance. Firstly, concerning on-line detection the advent of micro-fabricated flow-cells with inner volumes of only a few nL for transmission as well as attenuated total reflection measurements enabled on-line mid-IR detection in capillary LC and opened the path for the first successful realization of on-line mid-IR detection in capillary zone electrophoresis as well as micellar electrokinetic chromatography. Secondly, concerning off-line detection the use of micro-flow through dispensers now enables to concentrate eluting analytes on dried spots sized a few tens of micrometers, thus matching the dimensions for sensitive detection by mid-IR microscopy. Finally in an attempt to increase detection sensitivity of on-line mid-IR detection, mid-IR quantum cascade lasers have been used. Applications cover the field of food analysis, environmental analysis and the characterization of explosives among others. Best detection sensitivities for on-line and off-line detection have been achieved in miniaturized systems and are in the order of 50 ng and 2 ng on column, respectively.

Background Correction and Multivariate Curve Resolution of Online Liquid Chromatography with Infrared Spectrometric Detection

The use of multivariate curve resolution-alternating least-squares (MCR-ALS) in liquid chromatography-infrared detection (LC-IR) is troublesome due to the intense background absorption changes during gradient elution. Its use has been facilitated by previous removal of a significant part of the solvent background IR contributions due to common mobile phase systems employed during reversed phase gradient applications. Two straightforward background correction approaches based on simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) and principal component analysis (PCA) are proposed and evaluated on reversed phase gradient LC-IR data sets obtained during the analysis of carbohydrate and nitrophenol mixtures. After subtraction of the calculated background signal, MCR-ALS provided improved signal-to-noise ratios, removed remaining mobile phase and background signal contributions, and resolved overlapping chromatographic peaks. The present approach tends to enable easy-to-use background correction to facilitate the use of MCR-ALS in online LC-IR, even in challenging situations when gradient conditions are employed and only poor chromatographic resolution is achieved. It, therefore, shows great potential to facilitate the full exploitation of the advantages of simultaneous quantification and identification of a vast amount of analytes employing online IR detection, making new exciting applications more accessible.

New cut-off criterion for uninformative variable elimination in multivariate calibration of near-infrared spectra for the determination of heroin in illicit street drugs

A new cut-off criterion has been proposed for the selection of uninformative variables prior to chemometric partial least squares (PLS) modelling. After variable elimination, PLS regressions were made and assessed comparing the results with those obtained by PLS models based on the full spectral range. To assess the prediction capabilities, uninformative variable elimination (UVE)-PLS and PLS were applied to diffuse reflectance near-infrared spectra of heroin samples. The application of the proposed new cut-off criterion, based on the t-Students distribution, provided similar predictive capabilities of the PLS models than those obtained using the original criteria based on quantile value. However, the repeatability of the number of selected variables was improved significantly.

Differentiation of walnut wood species and steam treatment using ATR-FTIR and partial least squares discriminant analysis (PLS-DA).

AbstractWood is a ubiquitous material used in everyday life. Accurate identification of species can be of importance in a historical context enabling appropriate conservation treatment and adequate choice of material to be applied to historic wooden objects, and in a more modern context, in the identification of forgeries. Wood is also often treated to improve certain physical characteristics, often strength and durability. However, determination of whether or not a piece of wood has been treated can be very difficult. Infrared spectroscopy has previously been applied to differentiate between different wood species or between treated and untreated wood, often in conjunction with chemometric analysis techniques. Here, we report the use of mid-IR spectroscopy, coupled with partial least squares discriminant analysis for the discrimination between two walnut wood species and to differentiate between steam-treated and untreated samples of each of these wood species. We show that the discrimination between species and between steam-treated and non-steam-treated wood from Juglans nigra is very clear and, while analysis of the quality of the discrimination between steam-treated and non-steam-treated J. regia samples is not as good, it is, nevertheless, sufficient for discrimination between the two groups with a statistical significance of P < 0.0001. FigureATR-IR spectra of walnut wood from J. nigra and J. regia.

A rapid method for the differentiation of yeast cells grown under carbon and nitrogen-limited conditions by means of partial least squares discriminant analysis employing infrared micro-spectroscopic data of entire yeast cells

This paper shows the ease of application and usefulness of mid-IR measurements for the investigation of orthogonal cell states on the example of the analysis of Pichia pastoris cells. A rapid method for the discrimination of entire yeast cells grown under carbon and nitrogen-limited conditions based on the direct acquisition of mid-IR spectra and partial least squares discriminant analysis (PLS-DA) is described. The obtained PLS-DA model was extensively validated employing two different validation strategies: (i) statistical validation employing a method based on permutation testing and (ii) external validation splitting the available data into two independent sub-sets. The Variable Importance in Projection scores of the PLS-DA model provided deeper insight into the differences between the two investigated states. Hence, we demonstrate the feasibility of a method which uses IR spectra from intact cells that may be employed in a second step as an in-line tool in process development and process control along Quality by Design principles.

New background correction approach based on polynomial regressions for on-line liquid chromatography-Fourier transform infrared spectrometry.

In the present study a new approach for the chemometric background correction in on-line gradient LC-FTIR is introduced. For this purpose, the spectral changes of the elution mixture during gradient elution were analyzed applying 2D correlation spectroscopy. The fundamentals of the new background correction algorithm, based on polynomial fits calculated from a reference spectra matrix (Polyfit-RSM method) are explained. The Polyfit-RSM approach was applied on blank gradient runs as well as on LC-FTIR data obtained from the injection of a soft drink sample using acetonitrile:water as eluent. Results found were critically assessed and compared to those obtained by two previous background correction methods which are likewise based on the use of a reference spectra matrix (RSM). The Polyfit-RSM method provided lower noise levels throughout the whole spectral range than other alternative background correction methods, an excellent recovery of analyte spectra as well as chromatograms with a low noise level and also free from baseline shifts. A significant finding, which implies a major advantage for the practical applicability of the algorithm, is that the size of the RSMs can be reduced without affecting the accuracy of the correction method.

On-Line Fourier Transform Infrared Spectrometric Detection in Gradient Capillary Liquid Chromatography Using Nanoliter-Flow Cells

A capillary liquid chromatographic system has been successfully interfaced with a mid-IR Fourier transform infrared (FT-IR) spectrometer. Spectra were recorded on-line using a micromachined transmission CaF(2) cell (internal volume of 7.5 nL) that was placed on a dedicated beam condenser attached to the spectrometer. Linear gradients were run from (50:50) to (35:65) water (0.05% TFA)/acetonitrile in 15 min for the separation of standard solutions of four nitrophenols (4-nitrophenol, 3-methyl-4-nitrophenol, 2,4-dinitrophenol, and 2-nitrophenol) in a reversed phase system, providing limits of detection between 35 and 94 ng on-column. The changing background absorption due to gradient elution was successfully corrected by using a dedicated algorithm implemented in Matlab. When this chemometric data treatment was used, highly characteristic analyte spectra could be recorded as indicated by correlation coefficients between 89 and 95.8%, obtained when comparing mid-IR spectra of standard solutions and the spectra extracted from the chromatogram.

Modified locally weighted—Partial least squares regression improving clinical predictions from infrared spectra of human serum samples

Locally weighted partial least squares regression (LW-PLSR) has been applied to the determination of four clinical parameters in human serum samples (total protein, triglyceride, glucose and urea contents) by Fourier transform infrared (FTIR) spectroscopy. Classical LW-PLSR models were constructed using different spectral regions. For the selection of parameters by LW-PLSR modeling, a multi-parametric study was carried out employing the minimum root-mean square error of cross validation (RMSCV) as objective function. In order to overcome the effect of strong matrix interferences on the predictive accuracy of LW-PLSR models, this work focuses on sample selection. Accordingly, a novel strategy for the development of local models is proposed. It was based on the use of: (i) principal component analysis (PCA) performed on an analyte specific spectral region for identifying most similar sample spectra and (ii) partial least squares regression (PLSR) constructed using the whole spectrum. Results found by using this strategy were compared to those provided by PLSR using the same spectral intervals as for LW-PLSR. Prediction errors found by both, classical and modified LW-PLSR improved those obtained by PLSR. Hence, both proposed approaches were useful for the determination of analytes present in a complex matrix as in the case of human serum samples.

Urinary Lipid Peroxidation Byproducts: Are They Relevant for Predicting Neonatal Morbidity in Preterm Infants?

Preterm infants have an immature antioxidant system; however, they frequently require supplemental oxygen. Oxygen-free radicals cause both pulmonary and systemic inflammation, and they are associated with increased morbidity and mortality. Consequently, screening of metabolite profiles representing the amount of lipid peroxidation is considered of great relevance for the evaluation of in vivo oxidative stress and derived inflammation and damage. Ranges for total relative contents of isoprostanes (IsoPs), isofurans (IsoFs), neuroprostanes (NeuroPs), and neurofurans (NeuroFs) within targeted SpO2 ranges were determined in urine samples of 254 preterm infants<32 weeks of gestation within the frame of two randomized, controlled, and blinded clinical trials employing ultra-performance liquid chromatography-tandem mass spectrometry. A total of 536 serial urine samples collected during the first 4 weeks after birth in recruited infants who did not develop free radical associated conditions were analyzed. A reference range for lipid peroxidation byproducts, including isoprostanes, isofurans, neuroprostanes, and neurofurans, was calculated and possible correlations with neonatal conditions were investigated. Urinary elimination of isofurans in the first 4 days after birth correlated with later development of bronchopulmonary dysplasia. Our observations lead to the hypothesis that early urinary determination of lipid peroxidation byproducts, especially isofurans, is relevant to predict development of chronic lung conditions.

Analysis of lipid peroxidation biomarkers in extremely low gestational age neonate urines by UPLC-MS/MS

AbstractExtremely low gestational age neonates (ELGAN) frequently require the use of oxygen supply in the delivery room leading to systemic inflammation and oxidative stress that are responsible for increased morbidity and mortality. The objective of this study was to establish reference ranges of a set of representative isoprostanes and prostaglandins, which are stable biomarkers of lipid peroxidation often correlated with oxidative stress-related disorders. First, a quantitative ultra performance liquid chromatography—tandem mass spectrometry (UPLC-MS/MS) method was developed and validated. The proposed analytical method was tailored for its application in the field of neonatology, enabling multi-analyte detection in non-invasive, small-volume urine samples. Then, the lipid peroxidation product concentrations in a total of 536 urine samples collected within the framework of two clinical trials including extremely low gestational age neonates (ELGAN) were analyzed. The access to a substantially large number of samples from this very vulnerable population provided the chance to establish reference ranges of the studied biomarkers. Up to the present, and for this population, this is the biggest reference data set reported in literature. Results obtained should assist researchers and pediatricians in interpreting test results in future studies involving isoprostanes and prostaglandins, and could help assessing morbidities and evaluate effectiveness of treatment strategies (e.g., different resuscitation conditions) in the neonatal field. FigureOptimizing clinical outcomes in extremely low gestational age newborns by the determination of lipid peroxidation biomarkers in urine samples employing UPLC-MS/MS.