Label-Free Diagnosis of Pulmonary Fat Embolism Using Fourier Transform Infrared (FT-IR) Spectroscopic Imaging

The diagnosis of pulmonary fat embolism (PFE) is of great significance in the field of forensic medicine because it can be considered a major cause of death or a vital reaction. Conventional histological analysis of lung tissue specimens is a widely used method for PFE diagnosis. However, variable and labor-intensive tissue staining procedures impede the validity and informativeness of histological image analysis. To obtain complete information from tissues, a method based on infrared imaging of unlabeled tissue sections was developed to identify pulmonary fat emboli in the present study. We selected 15 PFE-positive lung samples and 15 PFE-negative samples from real cases. Oil red O (ORO) staining and infrared spectral imaging collection were both performed on all lung tissue samples. And the fatty tissue of the abdominal wall and the embolized lipid droplets in the lungs were taken for comparison. The results of the blind, evaluation by pathologists, showed good agreement between the infrared spectral imaging of the lung tissue and the standard histological stained images. Fourier transform infrared (FT-IR) spectroscopic imaging significantly simplifies the typical painstakingly laborious histological staining procedure. And we found a difference between lipid droplets embolized in abdominal wall fat and lung tissue.

Fourier Transform Infrared Spectroscopy and Vibrational Circular Dichroism Assisted Elucidation of the Solution-State Supramolecular Speciation in Racemic and Enantiopure Ketoprofen

The molecular structure and solution-state molecular interactions in the popular non-steroidal anti-inflammatory drug, ketoprofen, are extensively studied with the aim of gaining a better understanding of the chemical behavior of its solution state and its connection to its nucleation pathway and crystallization outcome. Using as reference solid-state X-ray structures of enantiomeric and racemic forms of ketoprofen, a set of self-assembly models underpinned by density functional theory calculations has been considered for the analysis of spectroscopic data, infrared (IR) and vibrational circular dichroism (VCD), obtained for solutions of the samples as a function of composition and solvent. From our results it can be concluded that, contrary to the general belief for generic carboxylic acids, there are no cyclic dimeric structures of ketoprofen present in solution, but rather linear arrays made up of two (in high polar or diluted media) or more units (in low polar or low dilution media). This observation is in line with the idea that the weak contacts (other than H-bonding) would hold the key to molecular self-assembly, in agreement with recent studies on other aromatic carboxylic acids.

Circular Dichroism Spectral Similarity Plots to Extend Validation and Correction to All Measured Wavelengths

Interlaboratory comparisons of circular dichroism (CD) spectra are useful for developing confidence in the measurements associated with optically active molecules. These measurements also help define the higher-order (secondary and tertiary) structure of biopolymers. Unfortunately, the extent of the validity of these measurements has been unclear. In this work, a method is described to extend CD validation over the entire observed wavelength range using what will be called spectral similarity plots. The method involves plotting, wavelength by wavelength, all measured spectral intensities of a sample at one concentration against the intensity values of the same material at a different concentration or pathlength. These spectral similarity plots validate the instrument in terms of spectral shape and whether the shape is shifted in intensity and/or in wavelength. This comparison tests the linearity of instrument’s signal, the balance of its left and right polarizations, its wavelengths, and its spectral intensity scales. When the process is applied to materials with accepted and archived intensity values, the method can be linked to older single-wavelength and double-wavelength calibration techniques. Further, spectral similarity testing of CD spectra from samples with different concentrations run in different labs suggests that improved interlaboratory validation of CD data is possible. Since a database of archival CD measurements is available online, spectral similarity comparisons could possibly provide the ability to compare linearity, polarization balance, wavelength, and spectral intensity between all current CD instruments. If the preliminary results published here prove robust and transferable, then comparisons of full-wavelength range spectra to archived data using spectral similarity plots should become part of the standard process to validate and calibrate the performance of CD instruments.

Quantitative Hydrogen Chloride Detection in Combustion Environments Using Tunable Diode Laser Absorption Spectroscopy with Comprehensive Investigation of Hot Water Interference

Hydrogen chloride (HCl) monitoring during combustion/gasification of biomass fuels and municipal solid waste, such as polyvinyl chloride (PVC) and food residues, is demanded to avoid the adverse effect of HCl to furnace operation and to improve the quality of the gas products. Infrared tunable diode laser absorption spectroscopy (IR-TDLAS) is a feasible nonintrusive in-situ method for HCl measurements in harsh environments. In the present work, the measurement was performed using the R(3) line of the ν2 vibrational band of HCl at 5739.25 cm–1 (1742.4 nm). Water vapor is ubiquitous in combustion/gasification environments, and its spectral interference is one of the most common challenges for IR-TDLAS. Spectral analysis based on the current well-known databases was found to be insufficient to achieve an accurate measurement. The lack of accurate temperature-dependent water spectra can introduce thousands parts per million (ppm) HCl overestimation. For the first time, accurate spectroscopic data of temperature-dependent water spectra near 5739.3 cm–1 were obtained based on a systematic experimental investigation of the hot water lines in a well-controlled, hot flue gas with a temperature varying from 1100 to 1950 K. With the accurate knowledge of hot water interference, the HCl TDLAS system can achieve a detection limit of about 100 ppm⋅m at around 1500 K, and simultaneously the gas temperature can be derived. The technique was applied to measure the temporally resolved HCl release and local temperature over burning PVC particles in hot flue gas at 1790 K.

Standoff Detection of Oil and Powder Mixtures at 12 Meters Using a Tunable Quantum Cascade Laser-Based System with a Close Focus Telescope and Uncooled Infrared Detector

We have designed and demonstrated a quantum cascade laser (QCL) based standoff system that utilizes an uncooled mercury cadmium telluride (MCT) detector with lock-in signal processing for chemical identification at a distance of 12.5 meters in indoor ambient light conditions. In the system, a tunable quad-QCL operating (1 MHz) in quasi-continuous wave mode between 8.45 and 10.03 μm (∼1182 to 1000 cm−1) serves as the active mid-infrared source for remotely interrogating mineral, powder, and thin film oil samples including powder mixtures (6, 12.5, 25, and 50%) of crystalline quartz (SiO2) in KBr. Light as reflected from a given sample is collected using a 10-inch (25.4 cm) Dall Kirkham telescope and coupled with ZnSe optics to an uncooled MCT detector. The mixture dependence of the highly transparent KBr and strongly absorbing quartz was found to fit a modified version of the Schatz reflectance model for compacted powder mixtures. All reflectance spectra reported are relative to an Au-coated diffuse reflector. A NIST traceable polystyrene standard reflector was also used to determine the QCL wavelength tuning range and calibration.

Beyond Beer’s Law: Quasi-Ideal Binary Liquid Mixtures

We have recorded attenuated total reflection infrared spectra of binary mixtures in the (quasi-)ideal systems benzene–toluene, benzene–carbon tetrachloride, and benzene–cyclohexane. We used two-dimensional correlation spectroscopy, principal component analysis, and multivariate curve resolution to analyze the data. The 2D correlation proves nonlinearities, also in spectral ranges with no obvious deviations from Beer’s approximation. The number of principal components is much higher than two and multivariate curve resolution carried out under the assumption of the presence of a third component, results in spectra which only show bands of the original components. The results negate the presence of third components, since any complex should have lower symmetry than the individual molecules and thus more and/or different infrared-active bands in the spectra. Based on Lorentz–Lorenz theory and literature values of the optical constants, we show that the nonlinearities and additional principal components are consequences of local field effects and the polarization of matter by light. Lorentz–Lorenz theory is, however, not able to explain, for example, the different blueshifts of the strong A2u band of benzene in the three mixtures. Obviously, infrared spectroscopy is sensitive to the short-range order around the molecules, which changes with content, their shapes, and their anisotropy.

Critical Evaluation of Spectral Resolution Enhancement Methods for Raman Hyperspectra

Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks. Furthermore, there is a need for automated methods to apply to large numbers of varied hyperspectral data sets containing multiple overlapping peaks, and thus methods ideally suitable for diverse tasks. To investigate these issues, we implemented three novel resolution enhancement methods based on pseudospectra, over-deconvolution, and peak fitting to evaluate them along with three extant methods: node narrowing, blind deconvolution, and the general-purpose peak fitting program Fityk. We first applied the methods to varied synthetic spectra, each consisting of nine overlapping Voigt profile peaks. Improved spectral resolution was evaluated based on several criteria including the separation of overlapping peaks and the preservation of true peak intensities in resolution-enhanced spectra. We then investigated the efficacy of these methods to improve the resolution of measured Raman spectra. High resolution spectra of glucose acquired with a narrow spectrometer slit were compared to ones using a wide slit that degraded the spectral resolution. We also determined the effects of the different resolution enhancement methods on 2D-COS and on chemical contrast image generation from mammalian cell spectra. We conclude with a discussion of the particular benefits, drawbacks, and potential of these methods. Our efforts provided insight into the need for effective resolution enhancement approaches, the feasibility of these methods for automation, the nature of the problems currently limiting their use, and in particular those aspects that need improvement.

Mesoporous Zirconia Coating for Sensing Applications Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy

Mid-infrared attenuated total reflection (ATR) spectroscopy is a powerful tool for in situ monitoring of various processes. Mesoporous silica, an extensively studied material, has already been applied in sensing schemes due to its high surface area and tunable surface chemistry. However, its poor chemical stability in aqueous solutions at pH values higher than 8 and strong absorption below 1250 cm−1 limits its range of applications. To circumvent these problems, a mesoporous zirconia coating on ATR crystals was developed. Herein, the synthesis, surface modification, and characterization of ordered mesoporous zirconia films on Si wafers and Si-ATR crystals are presented. The modified coating was applied in sensing schemes using aromatic and aliphatic nitriles in aqueous solution as organic pollutants. The mesoporous zirconia coating shows strong chemical resistance when kept in alkaline solution for 72 h. The success of surface modification is confirmed using Fourier transform infrared (FT-IR) spectroscopy and contact angle measurements. Benzonitrile and valeronitrile in water are used as model analytes to evaluate the enrichment performance of the film. The experimental results are fitted using Freundlich isotherms, and enrichment factors of 162 and 26 are calculated for 10 mg L−1 benzonitrile and 25 mg L−1 valeronitrile in water, respectively. Limits of detection of 1 mg L−1 for benzonitrile and 11 mg L−1 for valeronitrile are obtained. The high chemical stability of this coating allows application in diverse fields such as catalysis with the possibility of in situ monitoring using FT-IR spectroscopy.

Transmission Infrared Microscopy and Machine Learning Applied to the Forensic Examination of Original Automotive Paint

Alternate least squares (ALS) reconstructions of the infrared (IR) spectra of the individual layers from original automotive paint were analyzed using machine learning methods to improve both the accuracy and speed of a forensic automotive paint examination. Twenty-six original equipment manufacturer (OEM) paints from vehicles sold in North America between 2000 and 2006 served as a test bed to validate the ALS procedure developed in a previous study for the spectral reconstruction of each layer from IR line maps of cross-sectioned OEM paint samples. An examination of the IR spectra from an in-house library (collected with a high-pressure transmission diamond cell) and the ALS reconstructed IR spectra of the same paint samples (obtained at ambient pressure using an IR transmission microscope equipped with a BaF2 cell) showed large peak shifts (approximately 10 cm−1) with some vibrational modes in many samples comprising the cohort. These peak shifts are attributed to differences in the residual polarization of the IR beam of the transmission IR microscope and the IR spectrometer used to collect the in-house IR spectral library. To solve the problem of frequency shifts encountered with some vibrational modes, IR spectra from the in-house spectral library and the IR microscope were transformed using a correction algorithm previously developed by our laboratory to simulate ATR spectra collected on an iS-50 FT-IR spectrometer. Applying this correction algorithm to both the ALS reconstructed spectra and in-house IR library spectra, the large peak shifts previously encountered with some vibrational modes were successfully mitigated. Using machine learning methods to identify the manufacturer and the assembly plant of the vehicle from which the OEM paint sample originated, each of the twenty-six cross-sectioned automotive paint samples was correctly classified as to the “make” and model of the vehicle and was also matched to the correct paint sample in the in-house IR spectral library.