Roumiana Tsenkova

Aquaphotomics: Dynamic Spectroscopy of Aqueous and Biological Systems Describes Peculiarities of Water:

ISSn: 0967-0335

Comparison between Conventional Spectral Analysis Methods, Chemometrics, and Two-Dimensional Correlation Spectroscopy in the Analysis of Near-Infrared Spectra of Protein

The present study has aimed at comparing three methods for analyzing near-infrared (NIR) spectra: conventional spectral analysis methods, chemometrics, and generalized two-dimensional (2D) correlation spectroscopy. In a comparison of these approaches, NIR spectra were measured for aqueous solutions of human serum albumin (HSA) with the concentration range of 0.5–5.0 wt %. Synchronous and asynchronous 2D correlation spectra were generated from the concentration-dependent NIR spectral variations of HSA in distilled water. The first and second loadings plots were calculated for principal component analysis (PCA) models based upon the above NIR spectral data. It was found that slice spectra calculated from the synchronous spectra are very close to the first loadings plots and that slice spectra from the asynchronous spectra have a close resemblance to the second loadings plots. The reasons why the synchronous and asynchronous spectra bear close resemblance to the first and second loadings plots for the PCA model, respectively, are discussed in the paper.

NIR detection of honey adulteration reveals differences in water spectral pattern

High fructose corn syrup (HFCS) was mixed with four artisanal Robinia honeys at various ratios (0-40%) and near infrared (NIR) spectra were recorded with a fiber optic immersion probe. Levels of HFCS adulteration could be detected accurately using leave-one-honey-out cross-validation (RMSECV=1.48; R(2)CV=0.987), partial least squares regression and the 1300-1800nm spectral interval containing absorption bands related to both water and carbohydrates. Aquaphotomics-based evaluations showed that unifloral honeys contained more highly organized water than the industrial sugar syrup, supposedly because of the greater variety of molecules dissolved in the multi-component honeys. Adulteration with HFCS caused a gradual reduction of water molecular structures, especially water trimers, which facilitate interaction with other molecules. Quick, non-destructive NIR spectroscopy combined with aquaphotomics could be used to describe water molecular structures in honey and to detect a rather common form of adulteration.

Near infrared spectroscopy and aquaphotomics: novel approach for rapid in vivo diagnosis of virus infected soybean.

Near infrared spectroscopy with aquaphotomics as a novel approach was assessed for the diagnosis of soybean plants (Glycine max) infected with soybean mosaic virus (SMV) at latent symptomless stage of the disease. Near infrared (NIR) leaf spectra (in the range of 730-1025nm) acquired from soybean plants with and without the inoculation of SMV were used. Leaf samples from all plants were assayed with enzyme-linked immunosorbent assay (ELISA) to confirm the infection. Previously reported NIR band for water at 970nm and two new bands at 910nm and 936nm in the water specific region of NIR were found to be markedly sensitive to the SMV infection 2weeks prior to the appearance of visual symptoms on infected leaves. The spectral calibration model soft independent modeling of class analogy (SIMCA), predicted the disease with 91.6% sensitivity and 95.8% specificity when the second order derivative of the individual plant averaged spectra were used. The study shows the potential of NIR spectroscopy with its novel approach to elucidate latent biochemical and biophysical information of an infection as it allowed successful discrimination of SMV infected plant from healthy at the early symptomless stage of the disease.

Near-infrared spectra of serum albumin and γ-globulin and determination of their concentrations in phosphate buffer solutions by partial least squares regression

Abstract Near-infrared (NIR) spectra have been measured for albumin and γ-globulin in a powder state as well as in phosphate buffer solutions. The second derivative spectra of powder samples have been used to make assignments of NIR bands of the proteins. The second derivative spectra of albumin and γ-globulin are significantly different from each other in the band frequencies and relative intensities. The NIR spectra in the 1300–1850 nm region of the solutions have been subjected to partial least squares (PLS) regression analysis to develop chemometrics models which predict the concentrations of the proteins. The calibration for the albumin solutions in the concentration range of 0.1–8.0 g/dl has yielded a correlation coefficient ( R ) of 0.9995 and a standard error of calibration (SEC) of 0.207 g/dl. For the γ-globulin solutions in the concentration range of 0.1–6.0 g/dl, R of 0.9946 and SEC of 0.128 g/dl have been obtained. Regression coefficients (RCs) for the calibration models have been calculated for the first four factors. These RCs reflect the spectral variations in bands due to the proteins and in a water band near 1400 nm caused by the dissolution of the proteins. Moreover, the RCs have been compared with the NIR spectra of the proteins in the powder state. The positions of peaks in the RCs correspond well to those of bands in the NIR spectra of the proteins in the powder state. This suggests that the chemometrics models can pick up effectively the information about albumin and γ-globulin, even if the models have been constructed from the spectra of the proteins in the dilute solutions.

Near-infrared spectroscopy for biomonitoring: influence of somatic cell count on cow's milk composition analysis

The influence of milk with high somatic cell count on the accuracy of near-infrared spectroscopic determination of fat, protein and lactose content of non-homogenized milk was investigated. Transmittance spectra of 258 milk samples were obtained by the NIRSystem6500 spectrophotom eter in the 700–1100 nmregion. The best accuracy for fat, protein and lactose content determination was found for calibration equations, derived from samples with low somatic cell count (SCC). The standard error of prediction increased and the correlation coefficient decreased significantly, both when equations, derived fromsam ples with low SCC milk were used to predict the content of the examined components in samples with high SCC, and when equations, obtained for samples with high SCC were used to predict the content of the components in samples with low SCC. Therefore, milk samples with high SCC in a data set used for calibration or prediction highly influenced the accuracy of fat, protein and lactose determination. r 2001 Elsevier Science Ltd. All rights reserved.

Temperature-dependent near-infrared spectra of bovine serum albumin in aqueous solutions: spectral analysis by principal component analysis and evolving factor analysis.

Fourier transform near-infrared (FT-NIR) spectra have been measured for bovine serum albumin (BSA) in an aqueous solution (pH 6.8) with a concentration of 5.0 wt % over a temperature range of 45–85 °C. Not only conventional spectral analysis methods, such as second-derivative spectra and difference spectra, but also chemometrics, such as principal component analysis (PCA) and evolving factor analysis (EFA), have been employed to analyze the temperature-dependent NIR spectra in the 7500–5500 and 4900–4200 cm−1 regions of the BSA aqueous solution. Intensity changes of bands in the 7200–6600 cm−1 and 4650–4500 cm−1 regions in the difference spectra indicate variations of the hydration and secondary structure of BSA in the aqueous solution, respectively. The plot of a band intensity at 7080 cm−1 in the different spectra shows a clear turning point at 63 °C, revealing that a significant change in the hydration occurs at about 63 °C. The forward and backward eigenvalues (EVs) from EFA suggest that marked changes in the hydration and secondary structure of BSA take place in the temperature ranges of 61–65 °C and 59–63 °C, respectively. In addition, the temperature of 71 °C marked in the EFA plots may correspond to the onset temperature of increase in the intermolecular β-sheet structure.

Characterisation of hydrogen bond perturbations in aqueous systems using aquaphotomics and multivariate curve resolution-alternating least squares

Aquaphotomics is a new discipline that provides a framework for understanding changes in the structure of water caused by various perturbations, such as variations in temperature or the addition of solutes, using near infrared spectroscopy (NIRS). One of the main purposes of aquaphotomics is to identify water bands as main coordinates of future absorbance patterns to be used as biomarkers. These bands appear as consequence of perturbations in the NIR spectra. Curve resolution techniques may help to resolve and find new water bands or confirm already known bands. The aim of this study is to investigate the application of multivariate curve resolution-alternating least squares (MCR-ALS) to characterise the effects of various perturbations on the NIR spectra of water in terms of hydrogen bonding. For this purpose, the perturbations created by temperature change and the addition of four solutions of different ionic strength and Lewis acidity were studied (NaCl, KCl, MgCl(2) and AlCl(3), with concentrations ranging from 0.2 to 1 mol L(-1) in steps of 0.2 mol L(-1)). Transmission spectra of all salt solutions and pure water were obtained at temperatures ranging from 28 to 45°C. We have found that three distinct components with varying temperature dependence are present in water perturbed by temperature. The salt solutions studied exhibited similar trends with respect to the temperature perturbation, while the peak locations of their MCR-ALS pure components varied according to the ionic strength of the salt used.

A Novel Diagnostic Method for Human Immunodeficiency Virus Type-1 in Plasma by Near-Infrared Spectroscopy

Presently, the diagnosis of virus infections is based mainly on serological assays. Although polymerase chain reaction (PCR) and enzyme‐linked immunosorbent assay (ELISA) have been increasingly used for the diagnosis of such viral infections, the risk of transfusion‐transmitted blood‐borne viruses remains. Furthermore, PCR and ELISA are expensive and time‐consuming, and sometimes cause false‐positive or false‐negative results. Therefore, a rapid, accurate and cost‐effective diagnostic procedure is needed. We subjected plasma from individuals infected with human immunodeficiency virus type‐1 (HIV‐1), the causative agent of acquired immune deficiency syndrome (AIDS), as well as plasma from uninfected individuals as a control to near‐infrared (NIR) spectroscopy, which may provide a rapid diagnostic method for HIV‐1 infection without using any reagent. NIR spectra in the 600–1,000 nm region for plasma from pre‐serologically HIV‐1‐infected individuals and healthy donors were subjected to partial least squares (PLS) regression analysis and leave‐out cross‐validation to develop a multivariate model to estimate the concentration of HIV‐1. Simultaneously, the same plasma samples were examined for HIV‐1 p24 by ELISA. The results obtained by the NIR spectroscopy model for HIV‐1 yielded a good correlation with those obtained by the reference method (HIV‐1 p24 ELISA). These results suggest that NIR spectroscopy using plasma could provide a rapid, accurate, cost‐effective tool for large‐scale diagnosis of HIV‐1 infection.

Spectral pattern of urinary water as a biomarker of estrus in the giant panda

Near infrared spectroscopy (NIRS) has been successfully used for non-invasive diagnosis of diseases and abnormalities where water spectral patterns are found to play an important role. The present study investigates water absorbance patterns indicative of estrus in the female giant panda. NIR spectra of urine samples were acquired from the same animal on a daily basis over three consecutive putative estrus periods. Characteristic water absorbance patterns based on 12 specific water absorbance bands were discovered, which displayed high urine spectral variation, suggesting that hydrogen-bonded water structures increase with estrus. Regression analysis of urine spectra and spectra of estrone-3-glucuronide standard concentrations at these water bands showed high correlation with estrogen levels. Cluster analysis of urine spectra grouped together estrus samples from different years. These results open a new avenue for using water structure as a molecular mirror for fast estrus detection.