Structural changes of milk components during acid-induced coagulation kinetics as studied by synchronous fluorescence and mid-infrared spectroscopy

Dynamic oscillatory experiments and front-face synchronous fluorescence spectroscopy and mid-infrared (mid-IR) spectroscopy have been used to investigate structure evolution, at the macroscopic and molecular levels, during milk acidification kinetics. The studies were performed using skim milk, at two different temperatures (30 °C and 40 °C), to which was added glucono-δ-lactone (GDL) to generate different structural changes in casein micelles and gels. Synchronous fluorescence spectra were recorded in the 250-500 nm excitation wavelength range using an offset of 80 nm between the excitation and emission monochromators for each system during the 300 min acidification kinetics. The change in the fluorescence intensity at 281 nm reflects the pH-induced physicochemical changes of casein micelles and, in particular, structural changes in the micelles in the pH range 5.5-5.0. Regarding mid-infrared spectroscopy, the region located between 1700 and 1500 cm(-1), corresponding to the amide I and II bands, and the 1500-900 cm(-1) region, called the fingerprint region, were considered for the characterization of milk coagulation kinetics. Changes in the absorbance at 1063 cm(-1) as a function of pH for kinetics recorded at 30 °C and 40 °C reflected pH-induced phosphate dissolution in the pH range 5.5-5.0. Compared to rheometry, which reveals microstructure changes only in the gel state, spectroscopic methods make it possible to monitor molecular structure changes in micelles throughout the acidification processes.     

荧光谱及平行因子分析在芝麻油与芝麻香精鉴别中的应用

利用FS920荧光光谱仪测量21种芝麻油和同品牌不同批次2种芝麻香精共23个样品的荧光光谱,并对激发-发射荧光谱数据矩阵(EEMs)进行平行因子分析,确定了平行因子分析模型的因子数及各因子的物质基础。综合分析同步三维荧光谱、激发-发射三维荧光谱及其等高线光谱图,给出了芝麻油及芝麻香精的峰位、峰数和峰强等特征信息;应用平行因子模型建立了芝麻油及芝麻香精的3因子激发、发射光谱轮廓图和样本因子相对含量图。证实荧光光谱技术和平行因子分析法对芝麻油和芝麻香精进行分析和鉴别的有效性。     

Analysis of protein-based media commonly found in paintings using synchronous fluorescence spectroscopy combined with multivariate statistical analysis

The spectrofluorimetric analysis of protein-based binding media, which are commonly found as painting materials, is based on the detection of emissions from amino acids, as well as fluorescent degradation products that develop with aging. Laser-induced fluorescence spectroscopy, fluorescence excitation emission spectroscopy, and time-resolved fluorescence spectroscopy have all been employed in efforts to discriminate between commonly found proteinaceous binding media, including egg white, egg yolk, milk, and casein, as well as collagen-based glues from rabbit skin, ox bone, parchment, and fish. However, synchronous fluorescence spectroscopy (SFS), a rapid means of recording fluorescence properties of samples, has not been reported for the differentiation between binding media. This work focuses on the analysis of a large set of naturally aged films of different protein-based binding media using SFS with a range of different offsets between excitation and emission monochromators between 30-60 nm. An interpretation of synchronous fluorescence spectra of binding media is presented and is followed by an assessment and classification of a database of recorded spectra using multivariate analysis. Importantly, following SFS analysis of films of binding media, principal component analysis is used to differentiate among all the proteinaceous media considered on the basis of clustering of data. This application is thus a novel and nondestructive means for differentiation between protein-based binding media.     

Multiway Investigation of Interaction between Fluorescence Labeled DNA Strands and Unmodified Gold Nanoparticles

The single stranded DNA can be adsorbed on the negatively charged surface of gold nanoparticles (AuNPs), but the rigid structure of double stranded DNA prevents it from adsorption. Signal of a tagged single stranded DNA will be quenched by the plasmon effect of the AuNP surface after its adsorption. This phenomenon has been used to study the DNA hybridization and interactions of two complementary 21mer oligonucleotides each tagged with a different fluorescent dye in the presence of 13 nm gold nanoparticles. The DNA strands used in this study belong to the genome of HIV. The obtained rank deficient three-way fluorescence data sets were resolved by both PARAFAC and restricted Tucker3 models. This is the first successful application of a multiway chemometric technique to analyze multidimensional nanobiological data. The restricted Tucker3 showed a better performance compared to PARAFAC in resolving the data sets. The advantages of restricted Tucker3 analysis over the unrestricted one, i.e., the limited rotational freedom (more unique results) and better interpretability of the obtained results, were experienced in this study. The resolved excitation, emission, and concentration profiles and specially fluorescence resonance energy transfer (FRET) profiles obtained by restricted Tucker3 were chemically more meaningful than those obtained from PARAFAC.     

Two-dimensional multiwavelength fluorescence spectra of dipicolinic acid and calcium dipicolinate

Dipicolinic acid (DPA) and the Ca2+ complex of DPA (CaDPA) are major chemical components of bacterial spores. With fluorescence being considered for the detection and identification of spores, it is important to understand the optical properties of the major components of the spores. We report in some detail on the room-temperature fluorescence excitation and emission spectra of DPA and its calcium ion complex and provide a comparison of the excitation-emission spectrum in a dry, wet paste and aqueous form. DPA solutions have weak, if any, fluorescence, with increased fluorescence when the DPA is dry. After exposure to a broad source UV light of the DPA, wet or dry, we observe a large increase in fluorescence with a maximum intensity emission peak at around 440 nm for excitation light with a wavelength of around 360 nm. There is a slight blueshift in the absorption spectra of UV-exposed DPA from the unexposed DPA solution. CaDPA in solution shows a slight fluorescence with increased fluorescence in the dry form, and a substantial increase of fluorescence was observed after UV exposure with an emission peak of around 410 nm for excitation around 305 nm. The detailed excitation-emission spectra are necessary for better interpretation of the fluorescence spectra of bacterial spores where DPA is a major chemical component.     

Statistical analysis of excitation–emission matrices for laser-induced fluorescence spectroscopy

An algorithm for statistical processing of the set of multicomponent excitation–emission matrices for laser-induced fluorescence spectroscopy is proposed that is based on principal component analysis. It is shown for the first time that the fluorescence emission and excitation spectra of unknown fluorophores in optically thin samples can be calculated. Using the proposed algorithm, it is possible to pass from principal components with alternating signs to positive quantities corresponding to the spectra of real substances. The method is applied to a mixture of three fluorescent dyes, and it is demonstrated that the obtained spectra of principal components well reproduce the spectra of initial dyes.     

Multi-wavelength fluorescence-quenching model for determination of Cu2+ conditional stability constants and ligand concentrations of fulvic acid

In this work, a multi-wavelength model (MWM) is developed. It uses fluorescence bands in the fulvic acid (FA) spectrum that quench upon binding of inorganic Cu2+ to FA. Quenching data at pH values of 5, 6, and 7 are placed in sets, containing fluorescence measures at select wavelengths versus added copper (CM). Intensity data of wavelength set 1 are obtained from 25 nm constant offset synchronous fluorescence spectra (SyF), in which are observed distinct peaks (lambda(ex) = 415 nm, lambda(em) = 440 nm; and lambda(ex) = 471 nm, lambda(em) = 496 nm). Wavelength set 2 intensity data are obtained from the FA fluorescence excitation and emission maxima (lambda(ex) = 335 nm, lambda(em) = 450 nm; and X(ex) = 471 nm, lambda(em) = 496 nm). Application of MWM shows that the multi-wavelength data sets characterize ligands of different binding strength (log K(x)) and concentration (C(Lx)). Corresponding to pH values of 5, 6, and 7, mean and standard deviation values for wavelength set 1 are log K(415/440) = 4.66 (0.12), 5.03 (0.12), and 5.05 (0.08), log K(471/496) = 4.93 (0.06), 5.27 (0.11), and 5.39 (0.09), C(415/440) = 3.1 (1.5), 10.9 (4.5), and 7.9 (3.9) microM, C(471/496) = 14.3 (3.0), 1.7 (0.6), and 1.4 (0.5) microM. And for wavelength set 2, log K(335/450) = 4.50 (0.03), 4.96 (0.27), and 5.22 (0.08), log K(471/496) = 5.02 (0.04), 5.42 (0.32), and 5.71 (0.09), C(335/450) = 8.8 (0.5), 21.9 (7.9), and 18.7 (0.3) microM, C(471/496) = 21.0 (2.5), 7.17 (1.2), and 7.09 (0.3) micrpM. The ability of the 415/440 nm SyF transect to characterize the main excitation and emission maximum of FA at 335/440 nm is evaluated. Relatively low concentration values returned by the model for this transect (415/440 nm) suggest that it is not entirely illustrative of the maximum. The model predictive capability is verified at pH 6 with two fluorescing Cu2+ chelating organic compounds, L-tyrosine and salicylic acid. This test confirms that the model is capable of providing good estimates of equilibrium binding parameters from multi-wavelength measurements of a mixed ligand system.     

Multivariate curve resolution of synchronous fluorescence spectra matrices of fulvic acids obtained as a function of pH

Synchronous fluorescence spectra (excitation wavelength range between 280 and 510 nm and wavelength interval of 25 nm) of three samples of fulvic acids (FA) were obtained as a function of the pH, in the range from 2.0 to 10.5, and as a function of the FA concentration, in the range from 20 to 180 mg/L. FA were obtained from composted livestock materials (lsFA), composted sewage sludge (csFA), and Laurentian soil (laFA). Three-dimensional spectral matrices were obtained (wavelength, pH, and FA concentration) and multivariate curve resolution (MCR) was used to calculate spectra and fluorescence intensity profiles for the detected components. Cluster analysis of the calculated spectra showed the existence of similar and unique fluorescent properties in the three FA samples. Some of the calculated fluorescence intensity profiles have a shape compatible with acid-base species distribution diagrams, which allowed pKa values to be estimated, namely, a well-defined acid-base equilibrium with pKa 5.7 +/- 0.2 (lsFA), 6.9 +/- 0.4 (csFA), and 5.5 +/- 0.2 (laFA); and other acid-base systems not well defined with pKa at about 3.0 and 8.6. Other spectral variations revealed the existence of inner-filter effects or self-quenching as the concentration of FA increases.     

Characterization and matching of oil samples using fluorescence spectroscopy and parallel factor analysis

A novel approach for matching oil samples by fluorescence spectroscopy combined with three-way decomposition of spectra is presented. It offers an objective fingerprinting based on the relative composition of polycyclic aromatic compounds (PACs) in oils. The method is complementary to GC-FID for initial screening of oil samples but can also be used for prescreening in the field, onboard ships, using a portable fluorescence spectrometer. Parallel factor analysis (PARAFAC) was applied to fluorescence excitation-emission matrixes (EEMs) of heavy fuel oils (HFOs), light fuel oils, lubricating oils, crude oils, unknown oils, and a sample collected in the spill area two weeks after the Baltic Carrier oil spill (Denmark, 2001). A total of 112 EEMs were decomposed into a five-factor PARAFAC model using excitation wavelengths from 245 to 400 nm and emission wavelengths from 280 to 550 nm. The PARAFAC factors were compared to EEMs of PAC standards with two to five rings, and the comparisons indicate that each of the factors can be related to a mixture of PACs with similar fluorescence characteristics: a mixture of naphthalenes and dibenzothiophenes, fluorenes, phenanthrenes, chrysenes, and five-ring PACs, respectively. Oils were grouped in score plots according to oil type. Except for HFOs and crude oils, the method easily discriminated between the four oil types. Minor overlaps of HFOs and crude oils were observed along all five PARAFAC factors, and the variability of crude oils was large along factor 2 due to a varying content of five-ring PACs. The spill sample was correctly assigned as a HFO with similar PAC pattern as oil from the cargo tank of the Baltic Carrier by comparing the correlation coefficient of scores for the oil spill sample and possible source oils (i.e., oils in the database).     

Concise representation of mass spectrometry images by probabilistic latent semantic analysis

Imaging mass spectrometry (IMS) is a promising technology which allows for detailed analysis of spatial distributions of (bio)molecules in organic samples. In many current applications, IMS relies heavily on (semi)automated exploratory data analysis procedures to decompose the data into characteristic component spectra and corresponding abundance maps, visualizing spectral and spatial structure. The most commonly used techniques are principal component analysis (PCA) and independent component analysis (ICA). Both methods operate in an unsupervised manner. However, their decomposition estimates usually feature negative counts and are not amenable to direct physical interpretation. We propose probabilistic latent semantic analysis (pLSA) for non-negative decomposition and the elucidation of interpretable component spectra and abundance maps. We compare this algorithm to PCA, ICA, and non-negative PARAFAC (parallel factors analysis) and show on simulated and real-world data that pLSA and non-negative PARAFAC are superior to PCA or ICA in terms of complementarity of the resulting components and reconstruction accuracy. We further combine pLSA decomposition with a statistical complexity estimation scheme based on the Akaike information criterion (AIC) to automatically estimate the number of components present in a tissue sample data set and show that this results in sensible complexity estimates.     

Effect of washing on identification of Bacillus spores by principal-component analysis of fluorescence data

The fluorescence spectra of Bacillus spores are measured at excitation wavelengths of 280, 310, 340, 370, and 400 nm. When cluster analysis is used with the principal-component analysis, the Bacillus globigii spores can be distinguished from the other species of Bacillus spores (B. cereus, B. popilliae, and B. thuringiensis). To test how robust the identification process is with the fluorescence spectra, the B. globigii is obtained from three separate preparations in different laboratories. Furthermore the fluorescence is measured before and after washing and redrying the B. globigii spores. Using the cluster analysis of the first two or three principal components of the fluorescence spectra, one is able to distinguish B. globigii spores from the other species, independent of preparing or washing the spores.     

Principal component analysis of fluorescence changes upon growth conditions and washing of Pseudomonas aeruginosa

We have measured the autofluorescence from suspensions of Pseudomonas aeruginosa in the growth medium and after one, two, and three washes. The bacterium was grown in two different media, nutrient broth and King's B broth. The bacterium was harvested after 12, 24, and 48 h of growth. The fluorescence was measured with excitation every 10 nm from 200 nm to 600 nm. The fluorescence profiles were analyzed using principal component analysis. We found that most of the information is in the first three principal components. Stark differences in the value of the first principal component were noted between the samples in broth and those with one, two, or three washings. The second and third principal components noted differences between the samples washed once and those washed two or three times. There was no significant difference between samples washed two and three times. There are small differences noted between the samples grown in the two different broths, and no differences were noted among the samples harvested at different times.     

EEMizer: Automated modeling of fluorescence EEM data

For many years it has been known that PARAFAC offers a very attractive approach for modeling fluorescence excitation-emission matrices. Due to the uniqueness of the PARAFAC model and analogy between the structure of fluorescence data and the PARAFAC model, it is apparent that PARAFAC can resolve overlapping signals into pure spectra and relative concentrations under mild conditions. There are hundreds of applications exemplifying this, but still the use of PARAFAC has not spread from chemometrics to more main-stream analytical chemistry. Many reasons can be offered to explain this, but one seems to be that in practice it is difficult for chemometric novices to make use of PARAFAC. Selection of wavelengths, handling of scatter and of outliers are all issues that must be dealt with in order to build a good PARAFAC model. In this paper, a new algorithm called EEMizer is developed that aims to automate the use of PARAFAC. Through several examples it is shown how this algorithm can provide appealing PARAFAC models of data that would otherwise be hard to model.     

Fluorescence spectral analysis for the discrimination of complex, similar mixtures with the aid of chemometrics

An analytical method for the classification of complex real-world samples was researched and developed with the use of excitation-emission fluorescence matrix (EEFM) spectroscopy, using the medicinal herbs, Rhizoma corydalis decumbentis (RCD) and Rhizoma corydalis (RC) as example samples. The data set was obtained from various authentic RCD-A and RC-A, adulterated AD, and commercial RCD-C and RC-C samples. The spectra (range: λ(ex) = 215～395 nm and λ(em) = 290～560 nm), arranged in two- and three-way data matrix formats, were processed using principal component analysis (PCA) and parallel factor analysis (PARAFAC) to produce two-dimensional component-by-component plots for qualitative data classification. The RCD-A and RC-A object groups were clearly discriminated, but the AD and the RCD-C as well as RC-C samples were less well separated. PARAFAC analysis produced somewhat better discrimination, and loadings plots revealed the presence of the marker compound Protopine-a strongly fluorescing substance-as well as at least two other unidentified fluorescent components. Classification performance of the common K-nearest neighbors (KNN) and linear discrimination analysis (LDA) methods was relatively poor when compared with that of the back propagation- and radial basis function-artificial neural networks (BP-ANN and RBF-ANN) models on the basis of two- and three-way formatted data. The best results were obtained with the three-way fingerprints and the RBF-ANN model. Subsequently, the quality of the commercial samples (RCD-C and RC-C) was classified on the best optimized RBF-ANN model. Thus, EEFM spectroscopy, which provides three-way measured data, is potentially a powerful analytical technique for the analysis of complex real-world substances provided the classification is performed by the RBF-ANN or similar ANN methods.     

A procedure to facilitate the choice of the number of factors in multi-way data analysis applied to the natural samples: Application to monitoring the thermal degradation of oils using front-face fluorescence spectroscopy

Multi-way data analysis techniques are becoming ever more widely used to extract information from data, such as 3D excitation-emission fluorescence spectra, that are structured in (hyper-) cubic arrays. Parallel Factor Analysis (PARAFAC) is very commonly applied to resolve 3D-fluorescence data and to recover the signals corresponding to the various fluorescent constituents of the sample. The choice of the appropriate number of factors to use in PARAFAC is one of the crucial steps in the analysis. When the signals in the data come from a relatively small number of easily distinguished constituents, the choice of the appropriate number of factors is usually easy and the mathematical diagnostic tools such as the Core Consistency, in general give good results. However, when the data is from a set of natural samples, the core consistency may not be a good indicator for the choice of the appropriate number of factors.In this work, Multi-way Principal Component Analysis (MPCA) and the Durbin-Watson criterion (DW) are utilized to choose the number of factors to use in PARAFAC decomposition. This is demonstrated in a case where 3D-front-face fluorescence spectroscopy is used to monitor of the evolution of naturally occurring and neo-formed fluorescent components in oils during thermal treatment.     

三维荧光二阶校正法用于水样中培氟沙星和 氧氟沙星的同时测定

提出三维荧光二阶校正法,用于环境水样中氟喹诺酮类抗生素培氟沙星和氧氟沙星的同时定量分析.即在激发波长为230～400 nm,发射波长为360～580 nm范围内,测定样品(包含校正样、验证样、测试样)的三维荧光光谱,构建三维荧光响应数据阵;经数据处理后,采用交替三线性分解算法进行分解,得到与物质相关的相对激发、相对发射和相对浓度谱信息;通过对浓度信息进行单变量校正,获得校正曲线,进一步预测真实浓度.结果表明,培氟沙星和氧氟沙星的平均回收率分别为(101.1±5.3)％,(99.7±4.7)％,检测限分别为2.14,4.34 ng/mL,定量限分别为6.49,13.16 ng/mL.三维荧光二阶校正法可以在未知干扰物共存下,同时定量分析环境水样中培氟沙星和氧氟沙星,实现二阶优势.     

Changes in the luminescence between dried and wet bacillus spores

Fluorescence has been suggested as a method with which to detect and identify bacterial spores. To better understand the nature of the fluorescence signal, we observed the intrinsic steady-state fluorescence and phosphorescence spectra of Bacillus globigii (BG) in both dried and aqueous forms. In vitro, dried, and suspension forms of BG were measured at room temperature in 300-600-nm excitation wavelengths. Also, the phosphorescence of dry BG spores was measured at room temperature at 300-600-nm excitation wavelengths. The wet BG spores exhibited a strong maximum in their fluorescence spectrum, with the peak excitation wavelength near 300 nm and emission wavelength near 400 nm. When the BG was dried, this peak shifted to an approximately 450-nm excitation maximum and an 500-nm emission maximum. The difference between the wet and the dry spore fluorescence spectra cannot be explained by the phosphorescence of the dry spores. Other changes must take place when the spores are wet to account for the large changes observed in the spectrum.     

Three-way analysis of fluorescence spectra of polycyclic aromatic hydrocarbons with quenching by nitromethane

The application of trilinear decomposition (TLD) to the analysis of fluorescence excitation-emission matrices of mixtures of polycyclic aromatic hydrocarbons (PAHs) is described. The variables constituting the third-order tensor are excitation wavelength, emission wavelength, and concentration of a fluorescence quencher (nitromethane). The addition of a quencher to PAH mixtures selectively reduces the fluorescence intensity of mixture components according to the Stern-Volmer equation. TLD allows the three-way matrix to be decomposed to give unique solutions for the excitation spectrum, emission spectrum, and quenching profiles for each component. The availability of spectra and calculated Stern-Volmer constants can aid in the identification of unknown components. Preprocessing of the data to correct for Rayleigh/Raman scatter and primary absorption by the quencher is necessary. Both three-component (anthracene, pyrene, 1-methylpyrene) and four-component (fluoranthene, anthracene, pyrene, 2,3-benzofluorene) synthetic mixtures are successfully resolved by TLD using quencher concentrations up to 100 mM. Results are compared using both alternating least-squares and direct trilinear decomposition algorithms. The reproducibility of extracted Stern-Volmer constants is determined from replicate experiments. To illustrate the application of TLD to a real sample, a chromatographic cut from the analysis of a light gas oil sample was used. Analysis of the TLD extracted spectra and quenching constants suggests the presence of three classes of polycyclic aromatic hydrocarbons consistent with data from a second dimension of chromatography and mass spectrometry.     

Classification of organic and biological materials with deep ultraviolet excitation

We show that native fluorescence can be used to differentiate classes or groups of organic molecules and biological materials when excitation occurs at specific excitation wavelengths in the deep ultraviolet (UV) region. Native fluorescence excitation-emission maps (EEMs) of pure organic materials, microbiological samples, and environmental background materials were compared using excitation wavelengths between 200-400 nm with emission wavelengths from 270 to 500 nm. These samples included polycyclic aromatic hydrocarbons (PAHs), nitrogen- and sulfur-bearing organic heterocycles, bacterial spores, and bacterial vegetative whole cells (both Gram positive and Gram negative). Each sample was categorized into ten distinct groups based on fluorescence properties. Emission spectra at each of 40 excitation wavelengths were analyzed using principal component analysis (PCA). Optimum excitation wavelengths for differentiating groups were determined using two metrics. We show that deep UV excitation at 235 (+/-2) nm optimally separates all organic and biological groups within our dataset with >90% confidence. For the specific case of separation of bacterial spores from all other samples in the database, excitation at wavelengths less than 250 nm provides maximum separation with >6sigma confidence.     

Influence of mineral components on laser-induced fluorescence spectra of calcified human heart-valve tissues

Laser-induced fluorescence (LIF) spectra of calcified human heart-valve tissue and LIF spectra of macroscopic calcinosis fragments dissected from human heart valves were compared with LIF spectra of pig myocardium tissues. Excitation was provided by an excimer laser with wavelength lambda = 248 nm. Fluorescence bands that were due to mineral and organic tissue components were identified by measurement of LIF spectra of macroscopic fragments of calcified tissues that had been heat treated at 700 degrees C. The studies showed that LIF spectra of calcified tissues include fluorescence emission from tryptophan, collagen, elastin, and a mineral component of tissue, hydroxylapatite. The observed differences in LIF spectra of normal and calcified tissues with different pathologies may result not only from calcification-induced changes in relative collagen and elastin concentrations but also from additional (absent in normal heart tissue) fluorescence of hydroxylapatite. The calcification-induced changes in the LIF spectra of human heart-valve tissues, characterized by a 330/450 nm ratio, were found to be quite appreciable, which suggests that this ratio can be used with LIF measurements to evaluate the degree of heart-tissue calcification.