A novel tool for two-dimensional correlation spectroscopy

The contour map of a correlation matrix of two different spectroscopies applied to the same samples is a useful interpretation tool to establish relations between the two spectroscopies. The problem is that these maps are generally very complex. This paper describes a method to resolve the correlation contour map into a few spectroscopically meaningful submaps.     

Scanning fluorescence correlation spectroscopy: a tool for probing microsecond dynamics of surface-bound fluorescent species

In this report, a combined imaging and fluorescence correlation spectroscopy (FCS) method is described and its ability to characterize microsecond fluctuations in the fluorescence emission of a sample is demonstrated. A sample scanning laser confocal microscope is operated in the customary way while recording the time that each photon is detected with a time resolution of 50 ns using a low-cost counting board. The serial data stream of photon detection times allows access to fluorescence signal fluctuations that can be used to characterize dynamics using correlation methods. The same data stream is used to generate images of the sample. Using the technique, we demonstrate that it is possible to characterize the kinetics of transitions to and from nonemitting or "dark" states of the fluorescent dyes DiIC16 and ATTO 520. Results are similar to, but deviate slightly from, a model that has been frequently used for extracting singlet-triplet: conversion rates using conventional solution-based FCS. Like conventional FCS, the concentration, or in our case the areal density of coverage, of fluorescent species can also be obtained. Many single-molecule fluorescence experiments aim to extract kinetics from intensity trajectories; this method may be used as a rapid and convenient technique for characterization of surface-linked or thin-film samples prior to performing the more time and effort intensive single-molecule measurements. Besides the capacity to measure photophysical phenomena, the surface-sensitive FCS method could also be applied for measuring conformational changes or interaction kinetics for species immobilized on a surface. One possible scenario is measurements of the frequency and duration of association of ligand-receptor pairs where a fluorescently labeled component is freely diffusing and the other is surface immobilized. Given that microarrays of custom-designed, surface-immobilized peptides and nucleic acids are now readily available, the ability to sensitively measure association and dissociation rates of the surface-linked species with a freely diffusing species could be a useful extension to what has already become an extremely important tool for characterizing the interactions of biomolecules.     

Moving window two-dimensional correlation spectroscopy and determination of signal-to-noise threshold in correlation spectra

In this paper we report two new developments in two-dimensional (2D) correlation spectroscopy; one is the combination of the moving window concept with 2D spectroscopy to facilitate the analysis of complex data sets, and the other is the definition of the noise level in synchronous/asynchronous maps. A graphical criterion for the latter is also proposed. The combination of the moving window concept with correlation spectra allows one to split a large data matrix into smaller and simpler subsets and to analyze them instead of computing overall correlation. A three-component system that mimics a consecutive chemical reaction is used as a model for the illustration of the two ideas. Both types of correlation matrices, variable-variable and sample-sample, are analyzed, and a very good agreement between the two is met. The proposed innovations enable one to comprehend the complexity of the data to be analyzed by 2D spectroscopy and thus to avoid the risks of over-interpretation, liable to occur whenever improper caution about the number of co-existing species in the system is taken.     

Two-dimensional correlation spectroscopy: effect of reference spectrum on noise-free and noisy spectra

It has been shown that for two-dimensional (2D) correlation analysis with a perturbation average, the first or the last spectrum in the data set as a reference provides identical qualitative results. On the other hand, selection of the reference spectrum significantly different from the spectra used for 2D correlation analysis may complicate interpretation of the contour plots and in consequence lead to erroneous results. The effect of noise is relatively small when 2D correlation spectra are calculated without the reference spectrum. For the other reference spectra the magnitude of the noise effect is comparable. In all cases, the asynchronous spectra are more strongly affected by the noise as compared to the synchronous spectra.     

SIMULATE Program: a gamma ray spectroscopy tool

A software package which simulates the virtual creation of gamma ray spectra emitted from a combination of radioactive sources, as seen by a semiconductor or scintillation detector, is presented . It partially utilizes Monte Carlo techniques based on the physics of gamma ray spectroscopy. In addition, certain algorithms are used to compensate for the premature termination of the fate of the detected photons of any particular energy.     

Statistical two-dimensional correlation spectroscopy: its theory and applications to sets of vibrational spectra

The present study aims at developing a new form of two-dimensional (2D) correlation spectroscopy, statistical 2D correlation spectroscopy. Statistical 2D spectroscopy differs from the widely used generalized 2D correlation spectroscopy in that the former abstracts spectral features by pretreatment and by 2D maps that are limited by the correlation coefficients in the range from 1 to -1. In this paper, the theory of the new 2D method is briefly described, and then its applications are discussed to reveal spectral and concentration features of artificial model spectra, infrared spectra of polycondensation of bis(hydroxyethyl terephthalate) measured on-line, and short-wave near-infrared spectra of raw milk. The results are analyzed thoroughly and compared with those from generalized 2D correlation spectroscopy and partial least-squares loadings and scores. The most significant advantage of statistical 2D correlation spectroscopy is that the 2D correlation spectra are easy to calculate and are purely mathematical in nature, thereby eliminating any subjective involvement of an experimenter, while the inherent weakness of the method lies in its sensitivity to the noise.     

Statistical total correlation spectroscopy scaling for enhancement of metabolic information recovery in biological NMR spectra

The high level of complexity in nuclear magnetic resonance (NMR) metabolic spectroscopic data sets has fueled the development of experimental and mathematical techniques that enhance latent biomarker recovery and improve model interpretability. We previously showed that statistical total correlation spectroscopy (STOCSY) can be used to edit NMR spectra to remove drug metabolite signatures that obscure metabolic variation of diagnostic interest. Here, we extend this "STOCSY editing" concept to a generalized scaling procedure for NMR data that enhances recovery of latent biochemical information and improves biological classification and interpretation. We call this new procedure STOCSY-scaling (STOCSY(S)). STOCSY(S) exploits the fixed proportionality in a set of NMR spectra between resonances from the same molecule to suppress or enhance features correlated with a resonance of interest. We demonstrate this new approach using two exemplar data sets: (a) a streptozotocin rat model (n = 30) of type 1 diabetes and (b) a human epidemiological study utilizing plasma NMR spectra of patients with metabolic syndrome (n = 67). In both cases significant biomarker discovery improvement was observed by using STOCSY(S): the approach successfully suppressed interfering NMR signals from glucose and lactate that otherwise dominate the variation in the streptozotocin study, which then allowed recovery of biomarkers such as glycine, which were otherwise obscured. In the metabolic syndrome study, we used STOCSY(S) to enhance variation from the high-density lipoprotein cholesterol peak, improving the prediction of individuals with metabolic syndrome from controls in orthogonal projections to latent structures discriminant analysis models and facilitating the biological interpretation of the results. Thus, STOCSY(S) is a versatile technique that is applicable in any situation in which variation, either biological or otherwise, dominates a data set at the expense of more interesting or important features. This approach is generally appropriate for many types of NMR-based complex mixture analyses and hence for wider applications in bioanalytical science.     

Fluorescence correlation spectroscopy: an efficient tool for measuring size, size-distribution and polydispersity of microemulsion droplets in solution

Fluorescence correlation spectroscopy (FCS) is an ideal tool for measuring molecular diffusion and size under extremely dilute conditions. However, the power of FCS has not been utilized to its best to measure diffusion and size parameters of complex chemical systems. Here, we apply FCS to measure the size, and, most importantly, the size distribution and polydispersity of a supramolecular nanostructure (i.e., microemulsion droplets, MEDs) in dilute solution. It is shown how the refractive index mismatch of a solution can be corrected in FCS to obtain accurate size parameters of particles, bypassing the optical matching problem of light scattering techniques that are used often for particle-size measurements. We studied the MEDs of 13 different W(0) values from 2 to 50 prepared in a ternary mixture of water, sodium bis(2-ethylhexyl) sulfosuccinate (AOT), and isooctane, with sulforhodamine-B as a fluorescent marker. We find that, near the optical matching point of MEDs, the dynamic light scattering (DLS) measurements underestimate the droplet sizes while FCS estimates the accurate ones. A Gaussian distribution model (GDM) and a maximum-entropy-based FCS data fitting model (MEMFCS) are used to analyze the fluorescence correlation curves that unfold Gaussian-type size distributions of MEDs in solution. We find the droplet size varies linearly with W(0) up to ~20, but beyond this W(0) value, the size variation deviates from this linearity. To explain nonlinear variation of droplet size for W(0) values beyond ~20, we invoke a model (the coated-droplet model) that incorporates the size polydispersity of the droplets.     

Heteronuclear 19F-1H statistical total correlation spectroscopy as a tool in drug metabolism: study of flucloxacillin biotransformation

We present a novel application of the heteronuclear statistical total correlation spectroscopy (HET-STOCSY) approach utilizing statistical correlation between one-dimensional 19F/1H NMR spectroscopic data sets collected in parallel to study drug metabolism. Parallel one-dimensional (1D) 800 MHz 1H and 753 MHz 19F{1H} spectra (n = 21) were obtained on urine samples collected from volunteers (n = 6) at various intervals up to 24 h after oral dosing with 500 mg of flucloxacillin. A variety of statistical relationships between and within the spectroscopic datasets were explored without significant loss of the typically high 1D spectral resolution, generating 1H-1H STOCSY plots, and novel 19F-1H HET-STOCSY, 19F-19F STOCSY, and 19F-edited 1H-1H STOCSY (X-STOCSY) spectroscopic maps, with a resolution of approximately 0.8 Hz/pt for both nuclei. The efficient statistical editing provided by these methods readily allowed the collection of drug metabolic data and assisted structure elucidation. This approach is of general applicability for studying the metabolism of other fluorine-containing drugs, including important anticancer agents such as 5-fluorouracil and flutamide, and is extendable to any drug metabolism study where there is a spin-active X-nucleus (e.g., 13C, 15N, 31P) label present.     

Raman spectroscopy as a tool for measuring mutual-diffusion coefficients in hydrogels

Raman spectroscopy has been exploited to characterize the diffusion properties of solutes in hydrogels. Raman active vibrations were used as intrinsic probes of the solute concentration along gel cylinders. The resulting one-dimensional solute distribution, characterized as a function of both time and space, could be analyzed with a model based on Fick's diffusion law, and the mutual-diffusion coefficient (Dm) was then determined. To illustrate the potential of this approach, we measured the Dm of two polyethylene glycols (PEG) in Ca-alginate gels. In this case, the intensity of the CH stretching band was used to obtain the concentration profiles of PEGs, whereas the OH stretching band of water was used as an internal intensity standard. In addition to providing a straightforward approach to measuring diffusion coefficients, the Raman profile analysis provides information relative to the accessibility of gels to large molecules. As an example, it was found that the PEG penetration in Ca-alginate gels was restricted, a phenomenon that was dependent on PEG size. The Raman technique presented here effectively characterizes transport properties of solutes in gels, and such characterization is required for developing several technical applications of gels, such as their use as materials for controlled release of drugs.     

X-ray photoelectron spectroscopy: A powerful tool for a better characterization of thin film materials

X-ray photoelectron spectroscopy (XPS) is one of the most powerful tools to characterize thin films materials. To illustrate the use of XPS, some examples will be given on materials used as positive electrode in microbatteries. Further analyses of the film to understand the redox process are quite difficult with conventional methods due to the amorphous nature of the cathode. Here surface methods like XPS are very useful. Two main kinds of information can be obtained from XPS analysis: the oxidation states, and the determination of atomic environments. Different kinds of positive electrode materials were studied, titanium and molybdenum oxysulfides (MO _y S _z , M=Ti, Mo) and lithium cobalt oxide (Li _x CoO_2+y ) and have been illustrated in the present work. In light of the binding energies obtained for the reference compounds, several types of environments and different formal oxidation states have been found for the transition elements. XPS is also very useful for folllowing the oxydo-reduction mechanisms occurring during the intercalation and the de-intercalation of lithium, corresponding respectively to the discharge and the charge of the battery. After strict identification of each species, the evolution of their binding energies could be followed very easily. The XPS analyses of oxysulfides thin films at different stages of their cycling process have shown apparently good efficiency of the oxygen-rich compositions. During the redox process, the results obtained have clearly shown the important contribution of the sulfur atoms beside the transition metal atom.     

Near-infrared spectroscopy: a tool for monitoring submerged fermentation processes using an immersion optical-fiber probe

Near-infrared (NIR) spectroscopy has been developed as a noninvasive tool for the direct, real-time monitoring of glucose, lactic acid, acetic acid, and biomass in liquid cultures of microrganisms of the genera Lactobacillus and Staphylococcus. This was achieved employing a steam-sterilizable optical-fiber probe immersed in the culture (In-line Interactance System). Second-derivative spectra obtained were subjected to partial least-squares (PLS) regression and the results were used to build predictive models for each analyte of interest. Multivariate regression was carried out on two different sets of spectra, namely whole broth minus the spectral subtraction of water, and raw spectra. A comparison of the two models showed that the first cannot be properly applied to real-time monitoring, so this work suggests calibration based on non-difference spectra, demonstrating it to be sufficiently reliable to allow the selective determination of the analytes with satisfactory levels of prediction (standard error of prediction (SEP) < 10%). Direct interfacing of the NIR system to the bioreactor control system allowed the implementation of completely automated monitoring of different cultivation strategies (continuous, repeated batch). The validity of the in-line analyses carried out was found to depend crucially on maintaining constant hydrodynamic conditions of the stirred cultures because both gas flow and stirring speed variations were found to markedly influence the spectral signal.     

Applications of moving window two-dimensional correlation spectroscopy to analysis of phase transitions and spectra classification

Our recently proposed idea of moving window two-dimensional (2D) correlation spectroscopy, which partitions a data set into series of relatively small submatrices (windows) and calculates their covariance maps in succession, is tested for three convoluted data set. Phase-transition temperatures of oleic acid and poly-(N-isopropylacrylamide) in an aqueous solution are sought by analyzing covariances of their temperature-dependent near-infrared and infrared spectra, respectively, while Raman spectra of three kinds of polyethylene (PE) pellets are investigated to find the spectral differences among them and to classify randomly ordered spectra by a sample-sample (SS) covariance map. The criterion of mean of standard deviation of covariance matrices is used as an indicator of the crucial information present in these matrices so that only a few of them are discussed in details. The results are obtained quickly after very simple calculations and are studied at length. The baseline variation is not removed prior to the calculations but is found to be of use for the determination of the phase-transition temperatures. Randomly ordered Raman spectra of the PE pellets are classified by innovatively used and interpreted SS slice spectra, with the relation to principal component analysis discussed.     

Fluorescence correlation spectroscopy: a review of biochemical and microfluidic applications

Over the years fluorescence correlation spectroscopy (FCS) has proven to be a useful technique that has been utilized in several fields of study. Although FCS initially suffered from poor signal-to-noise ratios, the incorporation of confocal microscopy has overcome this drawback and transformed FCS into a sensitive technique with high figures of merit. In addition, tandem methods have evolved to include dual-color cross-correlation, total internal reflection fluorescence correlation, and fluorescence lifetime correlation spectroscopy combined with time-correlated single-photon counting. In this review, we discuss several applications of FSC for biochemical, microfluidic, and cellular investigations.     

Molecular recognition force spectroscopy: a new tool to tailor targeted nanoparticles

The density of targeting moieties in a nanoparticle-based gene-delivery system has been shown to play a fundamental role in its vectoring performance. Here, molecular recognition force spectroscopy is proposed as a novel screening tool to optimize the density of targeting moieties of functionalized nanoparticles towards attaining cell-specific interaction. By tailoring the nanoparticle formulation, the unbinding event probability between nanoparticles tethered to an atomic force microscopy tip and neuronal cells is directly correlated to the nanoparticle gene-vectoring capacity. Additionally, new insights into protein-receptor interaction are revealed. This novel approach opens new avenues in the field of nanomedicine.     

Near-edge X-ray absorption fine structure spectroscopy as a tool for investigating nanomaterials

We have demonstrated near-edge X-ray absorption fine structure (NEXAFS) spectroscopy as a particularly useful and effective technique for simultaneously probing the surface chemistry, surface molecular orientation, degree of order, and electronic structure of carbon nanotubes and related nanomaterials. Specifically, we employ NEXAFS in the study of single-walled carbon nanotube and multi-walled carbon nanotube powders, films, and arrays, as well as of boron nitride nanotubes. We have focused on the advantages of NEXAFS as an exciting, complementary tool to conventional microscopy and spectroscopy for providing chemical and structural information about nanoscale samples.     

Raman spectroscopy as a mapping tool for localized strain in microengineered structures

Abstracts are not published in this journal This revised version was published online in November 2006 with corrections to the Cover Date.