Multimodal Chemical Analysis of the Brain by High Mass Resolution Mass Spectrometry and Infrared Spectroscopic Imaging.

The brain functions through chemical interactions between many different cell types, including neurons and glia. Acquiring comprehensive information on complex, heterogeneous systems requires multiple analytical tools, each of which have unique chemical specificity and spatial resolution. Multimodal imaging generates complementary chemical information via spatially localized molecular maps, ideally from the same sample, but requires method enhancements that span from data acquisition to interpretation. We devised a protocol for performing matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance-mass spectrometry imaging (MSI), followed by infrared (IR) spectroscopic imaging on the same specimen. Multimodal measurements from the same tissue provide precise spatial alignment between modalities, enabling more advanced image processing such as image fusion and sharpening. Performing MSI first produces higher quality data from each technique compared to performing IR imaging before MSI. The difference is likely due to fixing the tissue section during MALDI matrix removal, thereby preventing analyte degradation occurring during IR imaging from an unfixed specimen. Leveraging the unique capabilities of each modality, we utilized pan sharpening of MS (mass spectrometry) ion images with selected bands from IR spectroscopy and midlevel data fusion. In comparison to sharpening with histological images, pan sharpening can employ a plethora of IR bands, producing sharpened MS images while retaining the fidelity of the initial ion images. Using Laplacian pyramid sharpening, we determine the localization of several lipids present within the hippocampus with high mass accuracy at 5 µm pixel widths. Further, through midlevel data fusion of the imaging data sets combined with k-means clustering, the combined data set discriminates between additional anatomical structures unrecognized by the individual imaging approaches. Significant differences between molecular ion abundances are detected between relevant structures within the hippocampus, such as the CA1 and CA3 regions. Our methodology provides high quality multiplex and multimodal chemical imaging of the same tissue sample, enabling more advanced data processing and analysis routines.

Dielectric Sphere Clusters as a Model to Understand Infrared Spectroscopic Imaging Data Recorded from Complex Samples.

Understanding the infrared (IR) spectral response of materials as a function of their morphology is not only of fundamental importance but also of contemporary practical need in the analysis of biological and synthetic materials. While significant work has recently been reported in understanding the spectra of particles with well-defined geometries, we report here on samples that consist of collections of particles. First, we theoretically model the importance of multiple scattering effects and computationally predict the impact of local particles' environment on the recorded IR spectra. Both monodisperse and polydisperse particles are considered in clusters with various degrees of packing. We show that recorded spectra are highly dependent on the cluster morphology and size of particles but the origin of this dependence is largely due to the scattering that depends on morphology and not absorbance that largely depends on the volume of material. The effect of polydispersity is to reduce the fine scattering features in the spectrum, resulting in a closer resemblance to bulk spectra. Fourier transform-IR (FT-IR) spectra of clusters of electromagnetically coupled poly(methyl methacrylate) (PMMA) spheres with wavelength-scale diameters were recorded and compared to simulated results. Measured spectra agreed well with those predicted. Of note, when PMMA spheres occupy a volume greater than 18% of the focal volume, the recorded IR spectrum becomes almost independent of the cluster's morphological changes. This threshold, where absorbance starts to dominate the signal, exactly matches the percolation threshold for hard spheres and quantifies the transition between the single particle and bulk behavior. Our finding enables an understanding of the spectral response of structured samples and points to appropriate models for recovering accurate chemical information from in IR microspectroscopy data.

Noninvasive Monitoring of Blood Glucose with Raman Spectroscopy.

The successful development of a noninvasive blood glucose sensor that can operate reliably over sustained periods of time has been a much sought after but elusive goal in diabetes management. Since diabetes has no well-established cure, control of elevated glucose levels is critical for avoiding severe secondary health complications in multiple organs including the retina, kidney and vasculature. While fingerstick testing continues to be the mainstay of blood glucose detection, advances in electrochemical sensing-based minimally invasive approaches have opened the door for alternate methods that would considerably improve the quality of life for people with diabetes. In the quest for better sensing approaches, optical technologies have surfaced as attractive candidates as researchers have sought to exploit the endogenous contrast of glucose, notably its absorption, scattering, and polarization properties. Vibrational spectroscopy, especially spontaneous Raman scattering, has exhibited substantial promise due to its exquisite molecular specificity and minimal interference of water in the spectral profiles acquired from the blood-tissue matrix. Yet, it has hitherto been challenging to leverage the Raman scattering signatures of glucose for prediction in all but the most basic studies and under the least demanding conditions. In this Account, we discuss the newly developed array of methodologies that address the key challenges in measuring blood glucose accurately using Raman spectroscopy and unlock new prospects for translation to sustained noninvasive measurements in people with diabetes. Owing to the weak intensity of spontaneous Raman scattering, recent research has focused on enhancement of signals from the blood constituents by designing novel excitation-collection geometries and tissue modulation methods while our attempts have led to the incorporation of nonimaging optical elements. Additionally, invoking mass transfer modeling into chemometric algorithms has not only addressed the physiological lag between the actual blood glucose and the measured interstitial fluid glucose values but also offered a powerful tool for predictive measurements of hypoglycemia. This framework has recently been extended to provide longitudinal tracking of glucose concentration without necessitating extensive a priori concentration information. These findings are advanced by the results of recent glucose tolerance studies in human subjects, which also hint at the need for designing nonlinear calibration models that can account for subject-to-subject variations in skin heterogeneity and hematocrit levels. Together, the emerging evidence underscores the promise of a blood withdrawal-free optical platform-featuring a combination of high-throughput Raman spectroscopic instrumentation and data analysis of subtle variations in spectral expression-for diabetes screening in the clinic and, ultimately, for personalized monitoring.

Less is more: Avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection.

Despite its intrinsic advantages, translation of laser induced breakdown spectroscopy for material identification has been often impeded by the lack of robustness of developed classification models, often due to the presence of spurious correlations. While a number of classifiers exhibiting high discriminatory power have been reported, efforts in establishing the subset of relevant spectral features that enable a fundamental interpretation of the segmentation capability and avoid the 'curse of dimensionality' have been lacking. Using LIBS data acquired from a set of secondary explosives, we investigate judicious feature selection approaches and architect two different chemometrics classifiers -based on feature selection through prerequisite knowledge of the sample composition and genetic algorithm, respectively. While the full spectral input results in classification rate of ca.92%, selection of only carbon to hydrogen spectral window results in near identical performance. Importantly, the genetic algorithm-derived classifier shows a statistically significant improvement to ca. 94% accuracy for prospective classification, even though the number of features used is an order of magnitude smaller. Our findings demonstrate the impact of rigorous feature selection in LIBS and also hint at the feasibility of using a discrete filter based detector thereby enabling a cheaper and compact system more amenable to field operations.

Discerning the differential molecular pathology of proliferative middle ear lesions using Raman spectroscopy.

Despite its widespread prevalence, middle ear pathology, especially the development of proliferative lesions, remains largely unexplored and poorly understood. Diagnostic evaluation is still predicated upon a high index of clinical suspicion on otoscopic examination of gross morphologic features. We report the first technique that has the potential to non-invasively identify two key lesions, namely cholesteatoma and myringosclerosis, by providing real-time information of differentially expressed molecules. In addition to revealing signatures consistent with the known pathobiology of these lesions, our observations provide the first evidence of the presence of carbonate- and silicate-substitutions in the calcium phosphate plaques found in myringosclerosis. Collectively, these results demonstrate the potential of Raman spectroscopy to not only provide new understanding of the etiology of these conditions by defining objective molecular markers but also aid in margin assessment to improve surgical outcome.

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy.

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93-98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance.

Multi-color reflectance imaging of middle ear pathology in vivo.

Otoscopic examination using white-light illumination has remained virtually unchanged for well over a century. However, the limited contrast of white-light otoscopy constrains the ability to make accurate assessment of middle ear pathology and is subject to significant observer variability. Here, we employ a modified otoscope with multi-color imaging capabilities for superior characterization of the middle ear constituents in vivo and for enhanced diagnosis of acute otitis media and cholesteatoma. In this pilot study, five patients undergoing surgery for tympanostomy tube placement and congenital cholesteatoma excision were imaged using the custom-designed multi-color video-rate reflectance imaging system. We show that the multi-color imaging approach offers an increase in image contrast, thereby enabling clear visualization of the middle ear constituents, especially of the tympanic membrane vascularity. Differential absorption at the multiple wavelengths provides a measure of biochemical and morphological information, and the rapid acquisition and analysis of these images aids in objective evaluation of the middle ear pathology. Our pilot study shows the potential of using label-free narrow-band reflectance imaging to differentiate middle ear pathological conditions from normal middle ear. This technique can aid in obtaining objective and reproducible diagnoses as well as provide assistance in guiding excisional procedures.

Emerging trends in optical sensing of glycemic markers for diabetes monitoring.

In the past decade, considerable attention has been focused on the measurement of glycemic markers, such as glycated hemoglobin and glycated albumin, that provide retrospective indices of average glucose levels in the bloodstream. While these biomarkers have been regularly used to monitor long-term glucose control in established diabetics, they have also gained traction in diabetic screening. Detection of such glycemic markers is challenging, especially in a point-of-care setting, due to the stringent requirements for sensitivity and robustness. A number of non-separation based measurement strategies were recently proposed, including photonic tools that are well suited to reagent-free marker quantitation. Here, we critically review these methods while focusing on vibrational spectroscopic methods, which offer highly specific molecular fingerprinting capability. We examine the underlying principles and the utility of these approaches as reagentless assays capable of multiplexed detection of glycemic markers and also the challenges in their eventual use in the clinic.

In vivo study of lipid accumulation in the microalgae marine diatom Thalassiosira pseudonana using Raman spectroscopy.

An in vivo non-invasive quantitative analysis technique was introduced for evaluating the fat composition of living marine diatoms by using Raman spectroscopy in conjunction with a chemometric method. This technique enabled the observation of real-time variations in individual lipids in diatom cells without specific treatment or fat extraction. A confocal Raman spectroscope was used to measure the marine centric diatom Thalassiosira (T.) pseudonana that was cultured under six stress conditions, and the spectral data of accumulated fatty acids were obtained. A model-based chemometrics technique, ordinary least square was then used to extract specific signals from Raman spectra obtained for a mixture of fatty acids. The levels of four major lipid moieties from diatoms were extracted simultaneously, including myristic acid, palmitic acid, palmitoleic acid, and eicosapentaenoic acid from the Raman spectra. These results indicate that Raman spectroscopy in conjunction with a chemometrics method is reliable for the quantitative determination of the lipid composition accumulated in the cells of marine diatoms.

Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information.

Vibrational spectroscopy has emerged as a promising tool for non-invasive, multiplexed measurement of blood constituents - an outstanding problem in biophotonics. Here, we propose a novel analytical framework that enables spectroscopy-based longitudinal tracking of chemical concentration without necessitating extensive a priori concentration information. The principal idea is to employ a concentration space transformation acquired from the spectral information, where these estimates are used together with the concentration profiles generated from the system kinetic model. Using blood glucose monitoring by Raman spectroscopy as an illustrative example, we demonstrate the efficacy of the proposed approach as compared to conventional calibration methods. Specifically, our approach exhibits a 35% reduction in error over partial least squares regression when applied to a dataset acquired from human subjects undergoing glucose tolerance tests. This method offers a new route at screening gestational diabetes and opens doors for continuous process monitoring without sample perturbation at intermediate time points.

Multiwavelength fluorescence otoscope for video-rate chemical imaging of middle ear pathology.

A common motif in otolaryngology is the lack of certainty regarding diagnosis for middle ear conditions, resulting in many patients being overtreated under the worst-case assumption. Although pneumatic otoscopy and adjunctive tests offer additional information, white light otoscopy has been the main tool for diagnosis of external auditory canal and middle ear pathologies for over a century. In middle ear pathologies, the inability to avail high-resolution structural and/or molecular imaging is particularly glaring, leading to a complicated and erratic decision analysis. Here, we propose a novel multiwavelength fluorescence-based video-rate imaging strategy that combines readily available optical elements and software components to create a novel otoscopic device. This modified otoscope enables low-cost, detailed and objective diagnosis of common middle ear pathological conditions. Using the detection of congenital cholesteatoma as a specific example, we demonstrate the feasibility of fluorescence imaging to differentiate this proliferative lesion from uninvolved middle ear tissue based on the characteristic autofluorescence signals. Availability of real-time, wide-field chemical information should enable more complete removal of cholesteatoma, allowing for better hearing preservation and substantially reducing the well-documented risks, costs and psychological effects of repeated surgical procedures.

Sequential identification of model parameters by derivative double two-dimensional correlation spectroscopy and calibration-free approach for chemical reaction systems.

A sequential identification approach by two-dimensional (2D) correlation analysis for the identification of a chemical reaction model, activation, and thermodynamic parameters is presented in this paper. The identification task is decomposed into a sequence of subproblems. The first step is the construction of a reaction model with the suggested information by model-free 2D correlation analysis using a novel technique called derivative double 2D correlation spectroscopy (DD2DCOS), which enables one to analyze intensities with nonlinear behavior and overlapped bands. The second step is a model-based 2D correlation analysis where the activation and thermodynamic parameters are estimated by an indirect implicit calibration or a calibration-free approach. In this way, a minimization process for the spectral information by sample-sample 2D correlation spectroscopy and kinetic hard modeling (using ordinary differential equations) of the chemical reaction model is carried out. The sequential identification by 2D correlation analysis is illustrated with reference to the isomeric structure of diphenylurethane synthesized from phenylisocyanate and phenol. The reaction was investigated by FT-IR spectroscopy. The activation and thermodynamic parameters of the isomeric structures of diphenylurethane linked through a hydrogen bonding equilibrium were studied by means of an integration of model-free and model-based 2D correlation analysis called a sequential identification approach. The study determined the enthalpy (ΔH = 15.25 kJ/mol) and entropy (TΔS = 13.20 kJ/mol) of C═O···H hydrogen bonding of diphenylurethane through direct calculation from the differences in the kinetic parameters (δΔ(‡)H, -TδΔ(‡)S) at equilibrium in the chemical reaction system.

Activation and thermodynamic parameter study of the heteronuclear C=O···H-N hydrogen bonding of diphenylurethane isomeric structures by FT-IR spectroscopy using the regularized inversion of an eigenvalue problem.

The doublet of the ν(C=O) carbonyl band in isomeric urethane systems has been extensively discussed in qualitative terms on the basis of FT-IR spectroscopy of the macromolecular structures. Recently, a reaction extent model was proposed as an inverse kinetic problem for the synthesis of diphenylurethane for which hydrogen-bonded and non-hydrogen-bonded C=O functionalities were identified. In this article, the heteronuclear C=O···H-N hydrogen bonding in the isomeric structure of diphenylurethane synthesized from phenylisocyanate and phenol was investigated via FT-IR spectroscopy, using a methodology of regularization for the inverse reaction extent model through an eigenvalue problem. The kinetic and thermodynamic parameters of this system were derived directly from the spectroscopic data. The activation and thermodynamic parameters of the isomeric structures of diphenylurethane linked through a hydrogen bonding equilibrium were studied. The study determined the enthalpy (ΔH = 15.25 kJ/mol), entropy (TΔS = 14.61 kJ/mol), and free energy (ΔG = 0.6 kJ/mol) of heteronuclear C=O···H-N hydrogen bonding by FT-IR spectroscopy through direct calculation from the differences in the kinetic parameters (δΔ(‡)H, -TδΔ(‡)S, and δΔ(‡)G) at equilibrium in the chemical reaction system. The parameters obtained in this study may contribute toward a better understanding of the properties of, and interactions in, supramolecular systems, such as the switching behavior of hydrogen bonding.

pH-Response Mechanism of p-Aminobenzenethiol on Ag Nanoparticles Revealed By Two-Dimensional Correlation Surface-Enhanced Raman Scattering Spectroscopy.

The existence of pH-dependent surface-enhanced Raman scattering (SERS) of p-aminobenzenethiol (PATP) on Ag nanoparticles has been confirmed by numerous studies, but its mechanism still remains to be clarified. Discussion of the mechanism is at a standstill because of the lack of a systematic investigation of the process behind the pH-induced variation of the PATP behavior. Two-dimensional correlation spectroscopy is one of the most powerful and versatile spectral analysis methods for investigating perturbation-induced variations in dynamic data. Herein, we have analyzed the pH-dependent behavior of PATP using a static buffer solution with pH ranging from 3.0 to 2.0. The order of the variations in the different vibrational intensities was carefully investigated based on 2D correlation SERS spectroscopy. These results have demonstrated that the very first step of the pH-response process involves protonation of the amine group. The pH-response mechanism revealed is an important new component to our understanding of the origin of the b2-type bands of PATP.

Modeling of isomeric structure of diphenyl urethane by FT-IR spectroscopy during synthesis from phenylisocyanate and phenol as an inverse kinetic problem.

Isomeric structure of diphenyl urethane during synthesis from phenylisocyanate and phenol has been investigated by modeling the reaction extent as an inverse kinetic problem, using FT-IR difference spectroscopy, to obtain structural information on the formation of the isomeric structure. The aim of this study was to determine the primary algebraic structures (an inverse problem), which describe the chemical reaction system in terms of spectroscopic observables. Moreover, a conventional description of the evolution of chemical species and of the change of moles of the observable species, as a function of time, was explored, defined in terms of the extent of reaction ξ and the reaction stoichiometries ν, based on the Jouguet-de Donder equation, for an invariant system in batch experiments. Two processes for diphenyl urethane with hydrogen bonding and their free form were identified. Experimental input for the identification is a matrix of in situ spectroscopic data A (FT-IR/ATR spectra measured during the reaction process) and a matrix of initial moles (N(0)). Subsequently, (1) the number of observable reactions present, (2) the change of moles and their extent of reactions ξ, (3) the reaction stoichiometries v, (4) the concentration of all observable species (C), and finally (5) the kinetic rate constants were determined. Meaningful extraction of such algebraic system information (an inverse algebraic problem) is a mandatory prerequisite for the subsequent detailed kinetic modeling (an inverse kinetic problem). This research opens up the possibility of modeling the extent of the reaction and performing a kinetic analysis of the hydrogen bonding in an organic system. Important information could be extracted, for understanding of different functions and interactions of hydrogen bonding in a supramolecular system.

Spectroscopic evidence of the mechanism involved in the cationic diglycidyl ether of bisphenol A curing with rare earth metal triflates.

The cross-linking of diglycidyl ether of bisphenol A (DGEBA) using three rare earth triflates as initiators (lanthanum, ytterbium, and scandium) was studied by in situ Fourier transform infrared (FT-IR) spectroscopy. Cationic ring opening of epoxides can proceed through two different mechanisms: activated monomer (AM) and active chain end (ACE). Using advanced chemometric methods such as perturbation-correlation moving-window two dimensional correlation spectroscopy (PCMW2D) and multivariate curve resolution-alternating least squares (MCR-ALS) it has been possible to obtain spectroscopic evidence of the two mechanisms. Traditionally, the demonstration of different mechanism pathways requires designing specific experiments. The novelty of the present study is to find, without a specific experimental design, spectroscopic evidence of the pathway of the polymerization process and to analyze the effect of these initiators, as well as the evolution of the species that takes part in the curing process by structural techniques such as attenuated total reflection (ATR) FT-IR.

A methodology to estimate concentration profiles from two-dimensional covariance spectroscopy applied to kinetic data.

Two-dimensional (2D) covariance analyses applied to spectroscopy data obtained while monitoring chemical processes allow exploring the chemical reactions involved. Some slices of the sample-sample covariance map are an approach to the concentration profiles of the reactive species and we present a novel methodology to identify them. The method overcomes problems habitually referenced in the application of this technique and it is based on the selection of spectral zones with similar standard deviation of the variables and row centering the spectra data in each zone. The slices are identified according to the correlation coefficient value. The method is illustrated using simulated spectra data set representatives of two model reactions A --> B and A --> I --> B. It has been applied to analyze the effect of rare earth metal triflate initiators in the cationic curing process of diglycidyl ether of bisphenol A with gamma-valerolactone. The number of significant slices found is equal to the number of reactive species. This is interesting information that can be used as an initial estimation to find profile concentrations using other methods such as multivariate curve resolution-alternating least squares (MCR-ALS).

MCR-ALS for sequential estimation of FTIR-ATR spectra to resolve a curing process using global phase angle convergence criterion.

Curing reactions include side and consecutive reactions while the polymer is growing. In this paper, we used multivariate curve resolution-alternating least squares (MCR-ALS) to obtain quantitative information about the concentration of the chemical species involved in these reactions. The cationic curing reaction between diglycidyl ether of bisphenol A (DGEBA) and gamma-valerolactone (gamma-VL) was monitored by infrared spectroscopy (FTIR-ATR). If the MCR-ALS method is to be used with recorded spectral data, the rank deficiency usually present in the data matrix needs to be overcome and the goodness of the results depends on the initial estimates of the chemical species involved in the reaction. Our strategy was to sequentially apply MCR-ALS in the time intervals where there is selectivity for some reactions and to use the error criterion based on the global phase angle to identify the optimal number of iterations in ALS. The estimated spectra were sequentially incorporated into the data matrix to overcome the rank deficiency. The MCR-ALS results are evaluated by the residuals and parameters such as lack of fit, the percentage of explained variance and the coefficient of dissimilarity between the recovered spectra and the spectra of the pure species, when it is possible. For intermediate species, the correspondence between the ALS spectra solution and the chemical knowledge of this species was also qualitatively evaluated. The goodness of the estimated concentration profile of the two reagents gamma-VL and DGEBA, was evaluated by the correlation coefficient value between the estimated profile and the profile obtained when the specific absorption bands were monitored at 1776 and 910 cm(-1), respectively for each reagent. The correlation coefficient values were 0.9954 and 0.9885, respectively.

Spectroscopic and quantitative analysis of spiroorthoester synthesis by two-dimensional correlation and multivariate curve resolution methods of NIR data.

The spiroorthoester synthesis includes several competitives reactions. A way of determining the reactions that are taking place and their sequential order, is presented. The reaction between the phenylglycidylether and gamma-butyrolactone to obtain a spiroorthoester has been monitored by near-infrared spectroscopy (NIR). In addition to the formation of the corresponding spiroorthoester, some parallel processes can occur. By means of two-dimensional correlation analysis, only one reaction is postulated, the one corresponding to the spiroorthoester formation. This was confirmed by recording the NMR spectra of the final product. Applying multivariate curve resolution-alternating least squares (MCR-ALS) to the NIR spectra obtained during the reaction, it has been possible to obtain the concentration values of the species involved in the reaction. The recovered spectra were compared with the experimentally recorded spectra for the reagents (phenylglycidylether, gamma-butyrolactone) and the final product (spiroorthoester) and the correlation coefficients were, in all cases, higher than 0.990. The maximum and minimum limits associated with the ALS solutions were calculated, making it possible to limit to a considerable extent the ambiguity that is characteristic of these curve resolution methods.