Applied Spectroscopy

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Nucleic acid fluorescent probes are playing increasingly important roles in biological sensing in recent years. In addition to the conventional functions of single-stranded DNA/RNA to hybridize with their complementary strands, affinity nucleic acids (aptamers) with specific target binding properties have also been developed, which has greatly broadened the application of nucleic acid fluorescent probes to the detection of a large variety of analytes, including small molecules, proteins, ions, and even whole cells. Another chemical property of nucleic acids is to act as substrates for various nucleic acid enzymes. This property can be utilized not only to detect those enzymes and screen their inhibitors, but also employed to develop effective signal amplification systems, which implies extensive applications. This review mainly covers the biosensing methods based on the above three types of nucleic acid fluorescent probes. The most widely used intensity-based biosensing assays are covered first, including nucleic acid probe-based signal amplification methods. Then fluorescence lifetime, fluorescence anisotropy, and fluorescence correlation spectroscopy assays are introduced, respectively. As a rapidly developing field, fluorescence imaging approaches are also briefly summarized.

A deep-ultraviolet (UV) Raman spectrometer with excitation source tunable from 193 to 210 nm has been built and characterized. The dispersion of the spectrometer over the entire range was measured and described theoretically. The relative sensitivity of the spectrometer was estimated using the integrated intensity ratio of two Raman bands of cyclohexane. Resonance Raman spectra of three formulated insulin products were measured and compared. A band-targeted entropy minimization algorithm was applied to the collected spectra for mixture analysis of insulin products. We conclude that it is feasible to develop robust qualitative methods for quality control of protein-based formulated drug using DUVRR spectroscopy.

Probing the specific hydrogen-bonding behavior of thermoplastic poly-urethane (TPU) blends using vibrational spectroscopies remains the sin qua non for understanding the link between hydrogen-bonding and phasesegregation behavior. However, current literature holds to more traditional univariate approaches when studying the morphologically interesting normal molecular vibrations of TPUs. In the present study, multivariate analysis, including principal component analysis (PCA) and principal component regression (PCR), is used to scrutinize the relevant Raman bands acquired from a binary mixture of analogous TPU copolymer blends. Considering the near identical behavior of selected spectral regions, PCA was capable of isolating linear and nonlinear composition-dependent trends on PC-scores plots. From here, the PC scores, extracted from wavelengths comprising the carbonyl stretching region (1681–1764 cm⁻¹), CH₂ deformations (1380–1500 cm⁻¹), aromatic stretch from the hard segment (1617 cm⁻¹), and amide II mixed band (1540 cm⁻¹), were used to explicitly predict the mole fraction of hard segment present in each blend using PCR. Spectral preprocessing, wavelength selection, and variable scaling were major factors in PCR accurately predicting the weight fraction of each copolymer in spite of the clearly evident, blend-specific spectroscopic behavior.

The capability to analyze and detect the composition of distant samples (minerals, organics, and chemicals) in real time is of interest for various fields including detecting explosives, geological surveying, and pollution mapping. For the past 10 years, the University of Hawaii has been developing standoff Raman systems suitable for measuring Raman spectra of various chemicals in daytime or nighttime. In this article we present standoff Raman spectra of various minerals and chemicals obtained from a distance of 120 m using single laser pulse excitation during daytime. The standoff Raman system utilizes an 8-inch Meade telescope as collection optics and a frequency-doubled 532 nm Nd: YAG laser with pulse energy of 100 mJ/pulse and pulse width of 10 ns. A gated intensified charge-coupled device (ICCD) detector is used to measure time-resolved Raman spectra in daytime with detection time of 100 ns. A gate delay of 800 ns (equivalent to target placed at 120 m distance) was used to minimize interference from the atmospheric gases along the laser beam path and near-field scattering. Reproducible, good quality single-shot Raman spectra of various inorganic and organic chemicals and minerals such as ammonium nitrate, potassium perchlorate, sulfur, gypsum, calcite, benzene, nitrobenzene, etc., were obtained through sealed glass vials during daytime. The data indicate that various chemicals could easily be identified from their Raman fingerprint spectra from a far standoff distance in real time using single-shot laser excitation.

Airborne silica dust (quartz) is common in coal mines and represents a respiratory hazard that can lead to silicosis, a potentially fatal lung disease. With an eye toward developing a portable monitoring device for rapid analysis of silica dust, laser-induced breakdown spectroscopy (LIBS) was used to quantify quartz in coal dust samples collected on filter media. Pure silica (Min-U-Sil™ 5), Georgia kaolin, and Pittsburgh-4 and Illinois-6 coal dusts were deposited separately and at multiple mass loadings onto 37-mm polyvinylchloride (PVC) filters. LIBS-generated silicon emission was monitored at 288.16 nm, and non-silica contributions to that signal from kaolinite were removed by simultaneously detecting aluminum. Measurements of the four samples were used to calculate limits of detection (LOD) for silicon and aluminum of approximately 0.08 lg/cm² and 0.05 μg/cm², respectively (corresponding to 0.16 μg/cm² and 0. 20 μg/cm² for silica and kaolinite, respectively). Relative errors of prediction are around 10%. Results demonstrate that LIBS can dependably quantify silica on filter samples of coal dust and confirm that accurate quantification can be achieved for very lightly loaded samples, which supports the potential application of LIBS for rapid, in-field monitoring.

Laser-induced breakdown spectroscopy (LIBS) is evaluated as a potential analytic technique for rapid screening and quality control of anti-diabetic tablets. This paper proposes a simple LIBS-based method for the quantitative analysis of two active pharmaceutical ingredients (APIs): metformin (Met) and glybenclamide (Gly). In order to quantify both APIs, chlorine (Cl) concentration was estimated by employing the Cl/Br optical emission ratio, where Br was introduced as internal standard. Calibration curves were prepared, achieving linearity higher than 99%. On the other hand, for comparison to the proposed method, an isocratic reversed-phase high-performance liquid chromatography (RP-HPLC) method was also developed for quantitative determination of the same analytes by ultraviolet (UV) detection. The chromatographic separation was achieved on a Phenomenex Hypersil C18, 250 mm X 4.6 mm, 5 μm column. The mobile phase was K₂HPO₄/H₃PO₄-CH₃OH and flow rate was 1.0 mL min⁻¹. The method is linear over a range of 10-60 μg mL⁻¹ for Gly and 5-30 μg mL⁻¹ for Met and the correlation coefficients were >0.99. Recoveries were found to be in the range of 95-101%. Furthermore, four different commercial brands of each active agent were evaluated by both proposed LIBS and chromatographic methods and results were compared with each other. The comparison was satisfactorily validated by analysis of variance (ANOVA).

In this paper we present a chemometric method of analysis leading to isolation of Fourier transform infrared (FT-IR) spectra of biomacromolecules (HEW lysozyme, ctDNA) affected by osmolytes (trimethylamine-N-oxide and N,N,N-trimethylglycine, respectively) in aqueous solutions. The method is based on the difference spectra method primarily used to characterize the structure of solvent affected by solute. The cyclical usage of factor analysis allows precise information to be obtained on the shape of “affected spectra” of analyzed biomacromolecules. “Affected spectra” of selected biomacromolecules give valuable information on their structure in the presence of the osmolytes in solution, as well as on the level of perturbation in dependence of osmolyte concentration. The method also gives a possibility of insight into the mechanism of interaction in presented types of systems. It can be easily adapted to various chemical and biochemical problems where vibrational or ultraviolet-visible (UV-Vis) spectroscopy is used.

We have developed a rapid, nondestructive analytical method that estimates the thickness of a surface polymer layer with high precision but unknown accuracy using a single attenuated total reflection Fourier transform infrared (ATR FT-IR) measurement. Because the method is rapid, nondestructive, and requires no sample preparation, it is ideal as a process analytical technique. Prior to implementation, the ATR FT-IR spectrum of the substrate layer pure component and the ATR FT-IR and real refractive index spectra of the surface layer pure component must be known. From these three input spectra a synthetic mid-infrared spectral matrix of surface layers 0 nm to 10 000 nm thick on substrate is created de novo. A minimum statistical distance match between a process sample's ATR FT-IR spectrum and the synthetic spectral matrix provides the thickness of that sample. We show that this method can be used to successfully estimate the thickness of polysulfobetaine surface modification, a hydrated polymeric surface layer covalently bonded onto a polyetherurethane substrate. A database of 1850 sample spectra was examined. Spectrochemical matrix-effect unknowns, such as the nonuniform and molecularly novel polysulfobetaine-polyetherurethane interface, were found to be minimal. A partial least squares regression analysis of the database spectra versus their thicknesses as calculated by the method described yielded an estimate of precision of ±52 nm.

Monolayers of terminal alkynes with long hydrocarbon chains C_nH_2n+₁C[CH (n = 10, 13, 16) were prepared on Si(100) substrates via thermally induced hydrosilylation and the surface orientation of the hydrocarbon chains was investigated by external reflection infrared spectroscopy. It was found that under rigorous exclusion of oxygen in the monolayer preparation process, all three compounds yield highly characteristic IR reflection spectra, consisting of upward-pointing v(CH₂) absorptions and downward-pointing v(CH₃) absorptions, indicative of a highly ordered anisotropic film structure. Via spectral simulations it was found that the methylene backbones (CH₂)_n in these films adopt a uniform, all-trans conformation with a tilt angle of about 30° toward the surface normal, whereas the chain termini are disordered and give an isotropic film surface composed of randomly oriented CH₃ groups. Lower quality films, which are hardly distinguishable from highly ordered films by other methods, but have been shown to exhibit inferior electrical properties, are clearly identified in their infrared (IR) spectra as partly disordered structures. External reflection IR therefore proves to be an exceptionally sensitive tool to detect structural defects in these monolayers.

Despite the existence of various methods to remove cosmic spikes from Raman data, only a few of them are suitable for process Raman spectroscopy. The disadvantages of these algorithms include increased analysis time, low accuracy of spike detection, or reliance on variable parameters that must be chosen by trial and error in each case. We demonstrate a novel approach to detecting cosmic spikes in process Raman data and validate it using a wide range of experimental data. This new method features a multistage spike recognition algorithm that is based on tracking sharp changes of intensity in the time domain. The algorithm effectively distinguishes cosmic spikes from random spectral noise and abrupt variations of Raman peaks, allowing accurate detection of both high and low intensity cosmic spikes. The procedure is free from variable user-defined parameters and operates reliably in a fully automated manner with a wide range of time-series process Raman data sets containing more than 40 to 50 spectra.

Deconvolution has become one of the most used methods for improving spectral resolution. Deconvolution is an ill-posed problem, especially when the point spread function (PSF) is unknown. Non-blind deconvolution methods use a predefined PSF, but in practice the PSF is not known exactly. Blind deconvolution methods estimate the PSF and spectrum simultaneously from the observed spectra, which become even more difficult in the presence of strong noise. In this paper, we present a semi-blind deconvolution method to improve the spectral resolution that does not assume a known PSF but models it as a parametric function in combination with the a priori knowledge about the characteristics of the instrumental response. First, we construct the energy functional, including Tikhonov regularization terms for both the spectrum and the parametric PSF. Moreover, an adaptive weighting term is devised in terms of the magnitude of the first derivative of spectral data to adjust the Tikhonov regularization for the spectrum. Then we minimize the energy functional to obtain the spectrum and the parameters of the PSF. We also discuss how to select the regularization parameters. Comparative results with other deconvolution methods on simulated degraded spectra, as well as on experimental infrared spectra, are presented.

Spatially offset visible–near-infrared (VIS-NIR) spectroscopy was used to analyze of chemical compositions of the scattering liquids in the visible and near-infrared region from 530 to 930 nm. An experimental setup was designed based on a supercontinuum white-light laser source, an electrically controlled translation stage, and a high-performance spectrometer. The spatially offset spectra of the scattering liquids (composed of diluted Intralipid® 20% in distilled water) were measured at 24 sequential positions in the radial distribution from the incident light. A partial least squares regression method was applied to obtain the Intralipid® concentration from the spatially offset spectra. The results showed that the prediction accuracy of the Intralipid® concentration obtained from the spectra collected at multiple sample points was better than that obtained from the spectra collected at a single sample point. The coefficient of determination in the prediction set is 0.9835 at the optimized number of sample points.

Kidney stones were analyzed using laser-induced breakdown spectroscopy (LIBS), utilizing a high resolution multi-channel charge-coupled device (CCD) spectrometer and a nanosecond-pulse Nd: YAG laser. The kidney stones were also characterized using X-ray diffraction (XRD) and X-ray fluorescence (XRF) techniques for comparative analysis. It was found that the ratio of hydrogen (H) to carbon (C) was an important indicator of organic compounds such as uric acid. Advantages of LIBS, especially with regards to amount of sample required and sample preparation as well as the ability to carry out elemental analysis and classification of kidney stones simultaneously, over other analytical techniques such as XRD and XRF are discussed. The common minor elements detected in the kidney stones include P, S, Si, Ti, and Zn. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of broadband LIBS spectra were employed for classifying different types of kidney stones. The results are beneficial in understanding kidney stone formation processes, which can lead to preventive therapeutic strategies and treatment methods for urological patients.

Spectral scans of atomic line emission sources with a Shimadzu UV2101PC spectrophotometer show that the nominal wavelength depends upon the instrumental slit width, the wavelength sampling interval, and for some slit widths, also on the specified spectral range. The range dependence is manifested as a smoothing that occurs when the range includes >65 sampled wavelengths, and it affects both the wavelength and the line shape. For spectra not subject to this smoothing, the wavelength error looks like a one-sample misassociation of the wavelength and photometric readings. However, the instrument does reliably move to a specified wavelength, independent of the scan parameter settings. These behaviors do not seem to be documented anywhere but have been present in the software for operating this instrument for about two decades.