Model‐based pre‐processing in Raman spectroscopy of biological samples

Model‐based pre‐processing has become wide spread in spectroscopy and is the standard procedure in Fourier‐transform infrared spectroscopy. It has also been shown to give valuable contributions in Raman spectroscopy. Extended multiplicative signal correction is flexible enough to handle varying fluorescence background and take into account individual variations in baselines while still keeping enough rigidity through reference spectra and model fitting to avoid degenerate solutions and overfitting, when used correctly. We demonstrate the basic extended multiplicative signal correction method and some extensions, including a novel shift correction, on real Raman data to demonstrate effects on visual appearance, replicate variation and prediction. Comparisons with other standard correction methods are also shown and discussed. © 2016 The Authors. Journal of Raman Spectroscopy Published by John Wiley & Sons, Ltd.     

Raman spectroscopy of complex defined media: biopharmaceutical applications

We demonstrate the detection of glucose and lactate concentrations with high accuracy in the supernatants of Chinese hamster ovary (CHO) cell culture, grown in shake flasks in batch fermentation mode, using Raman spectroscopy and explicit model‐based classical least squares (CLS) algorithm. A deterministic Raman spectral library of pure components was created by acquiring Raman spectra from credible nutrient media constituents and CHO cell culture metabolites. Only analytes present with concentration above the instrument detection limit were included in this library. Residuals obtained after CLS analyses were used to identify missing components and to generate a revised library. An algorithmic sieve was thus construed to obtain an appropriate Raman spectral library from a complex chemical mixture that is well‐defined but an industrial secret. High performance liquid chromatography (HPLC) was used to provide reference glucose and lactate concentrations. [Correction added on 30 April 2015, after first online publication: the last three sentences of the abstract (previously stated in the abstract) have been deleted]. Copyright © 2015 John Wiley & Sons, Ltd.     

SVD‐based method for intensity normalization,background correction and solvent subtraction in Raman spectroscopy exploiting the properties of water stretching vibrations

A semiautomated method combining intensity normalization with effective elimination of the solvent signal and non‐Raman background is presented for Raman spectra of biochemical and biological analytes in aqueous solutions. The method is particularly suitable for rapid and effortless preprocessing of extensive datasets taken as a function of gradually varied physicochemical parameters, e.g. analyte and/or ligand concentration, temperature, pH, pressure, ionic strength, time, etc. For intensity normalization, the strong Raman OH stretching band of water in the range of 2700–3900 cm⁻¹ recorded together with the analyte spectrum in the fingerprint region below 1800 cm⁻¹ is employed as internal intensity standard. Concomitant dependences of the solvent Raman spectra are taken into account and, in some cases, turned into advantage. Once the Raman spectra of the solvent are acquired for a particular range of the parameter varied, solvent contribution can be subtracted correctly from any analyte spectrum taken within this range. The procedure presented can be efficiently applied only for the analytes having their own Raman signal in the range of OH stretching vibrations much weaker than that of the solvent. However, this is the case for a great number of biochemical and biological samples. Accuracy, reliability and robustness of the method were tested under the conditions of spontaneous Raman, resonance Raman and surface‐enhanced Raman scattering. Serviceability of the method is demonstrated by several real‐world examples. Copyright © 2011 John Wiley & Sons, Ltd.     

The characteristics of laser‐driven shock wave investigated by time‐resolved Raman spectroscopy

An accurate and simple method, Raman peak‐shift simulation, is proposed to determine the characteristics of a laser‐driven shock wave. Using the principle of the Raman peaks shifting at high pressure and the pressure distribution in the gauge layer, the profile of the Raman peak can be numerically simulated. Combined with time‐resolved Raman spectroscopy, some main characteristics of the shock wave were determined. In the experiment, polycrystalline anthracene was used as the pressure gauge. The pump–probe technique was used to obtain the time‐resolved Raman spectra of anthracene under shock loading. The velocity of the shock wave, the peak pressure and the rise time of the shock front were determined by simulating the experimental spectra numerically. The result shows that the method of Raman peak‐shift simulation is effective in obtaining the characteristics of a laser‐driven shock wave. Copyright © 2010 John Wiley & Sons, Ltd.     

Improved methods for fluorescence background subtraction from Raman spectra

Raman spectroscopy has attracted interest as a non‐invasive optical technique to study the composition and structure of a wide range of materials at the microscopic level. The intrinsic fluorescence background can be orders of magnitude stronger than the Raman scattering, and so, background removal is one of the foremost challenges for quantitative analysis of Raman spectra in many samples. A range of methods anchored in instrumental and computational programming approaches have been proposed for removing fluorescence background signals. An enhanced adaptive weighting scheme for automated fluorescence removal is reported, applicable to both polynomial fitting and penalized least squares approaches. Analysis of the background fitting results for ensembles of simulated spectra suggests that the method is robust and reliable and can significantly improve the background fit over the range of signal, shot noise and background parameters tested, while reducing the subjective nature of the process. The method was also illustrated by application to experimental data generated from aqueous solutions of bulk protein fibrinogen mixed with dextran. Copyright © 2013 John Wiley & Sons, Ltd.     

Non‐invasive depth profiling by space and time‐resolved Raman spectroscopy

Time‐resolved Raman spectroscopy, spatially offset Raman spectroscopy and time‐resolved spatially offset Raman spectroscopy (TR‐SORS) have proven their capability for the non‐invasive profiling of deep layers of a sample. Recent studies have indicated that TR‐SORS exhibits an enhanced selectivity toward the deep layers of a sample. However, the enhanced depth profiling efficiency of TR‐SORS, in comparison with time‐resolved Raman spectroscopy and spatially offset Raman spectroscopy, is yet to be assessed and explained in accordance to the synergistic effects of spatial and temporal resolutions. This study provides a critical investigation of the depth profiling efficiency of the three deep Raman techniques. The study compares the efficiency of the various deep Raman spectroscopy techniques for the stand‐off detection of explosive precursors hidden in highly fluorescing packaging. The study explains for the first time the synergistic effects of spatial and temporal resolutions in the deep Raman techniques and their impact on the acquired spectral data. Copyright © 2013 John Wiley & Sons, Ltd.     

A comparison of noise models in a hybrid reference spectrum and principal components analysis algorithm for Raman spectroscopy

Raman spectroscopy exploits the Raman scattering effect to analyze chemical compounds with the use of laser light. Raman spectra are most commonly analyzed using the ordinary least squares (LS) method. However, LS is known to be sensitive to variability in the spectra of the analyte and background materials. In a previous paper, we addressed this problem by proposing a novel algorithm that models expected variations in the analyte as well as background signals. The method was called the hybrid LS and principal component analysis (HLP) algorithm and used an unweighted Gaussian distribution to model the noise in the measured spectra. In this paper, we show that the noise in fact follows a Poisson distribution and improve the noise model of our hybrid algorithm accordingly. We also approximate the Poisson noise model by a weighted Gaussian noise model, which enables the use of a more efficient solver algorithm. To reflect the generalization of the noise model, we from hereon call the method the hybrid reference spectrum and principal components analysis (HRP) algorithm. We compare the performance of LS and HRP with the unweighted Gaussian (HRP‐G), Poisson (HRP‐P), and weighted Gaussian (HRP‐WG) noise models. Our experiments use both simulated data and experimental data acquired from a serial dilution of Raman‐enhanced gold‐silica nanoparticles placed on an excised pig colon. When the only signal variability was zero‐mean random noise (as examined using simulated data), HRP‐P consistently outperformed HRP‐G and HRP‐WG, with the latter coming in as a close second. Note that in this scenario, LS and HRP‐G were equivalent. In the presence of random noise as well as variations in the mean component spectra, the three HRP algorithms significantly outperformed LS, but performed similarly among themselves. This indicates that, in the presence of significant variations in the mean component spectra, modeling such variations is more important than optimizing the noise model. It also suggests that for real data, HRP‐WG provides a desirable trade‐off between noise model accuracy and computational speed. Copyright © 2013 John Wiley & Sons, Ltd.     

Surface‐enhanced Raman spectroscopy for trace‐level detection of explosives

The detection of explosives and their associated compounds for security screening is an active area of research and a wide variety of detection methods are involved in this very challenging area. Surface‐enhanced Raman scattering (SERS) spectroscopy is one of the most sensitive tools for the detection of molecules adsorbed on nano‐scale roughened metal surface. Moreover, SERS combines high sensitivity with the observation of vibrational spectra of species, giving complete information on the molecular structure of material under study. In this paper, SERS was applied to the detection of very small quantities of explosives adsorbed on industrially made substrates. The spectra were acquired with a compact Raman spectrometer. Usually, a high signal‐to‐noise (S/N) spectrum, suitable for identification of explosive molecules down to few hundreds of picograms, was achieved within 30 s. Our measurements suggest that it is possible to exploit SERS using a practical detection instrument for routine analysis. Copyright © 2010 John Wiley & Sons, Ltd.     

Detection of melamine in liquid milk using surface‐enhanced Raman scattering spectroscopy

Melamine, a nitrogen‐rich chemical, has recently caused enormous economic losses to the food industry due to the cases of milk products adulterated by melamine. This has led to an urgent need of rapid and reliable methods for detection of melamine in food. In this study, surface‐enhanced Raman scattering (SERS) spectroscopy was used to detect melamine in liquid milk. The sample preparation with liquid milk is very easy; it has to be only diluted with double‐distilled water followed by centrifugation. By using a silver colloid, at least a 10⁵‐fold enhancement of the Raman signal was achieved for the measurement of melamine. The limit of detection by this method was 0.01 µg ml⁻¹ for melamine standard samples. Based on the intensity of the Raman vibrational bands normalised to that of the band at 928 cm⁻¹ (CH₂), an external standard method was employed for quantitative analysis. The linear regression square (R²) of the curve was 0.9998; the limit of quantitation using this approach was 0.5 µg ml⁻¹ of melamine in liquid milk; the relative standard deviation was ≤10%; and recoveries were from 93 to 109%. The test results for SERS were very precise and as good as those obtained by liquid chromatography/tandem mass spectrometry. The method was simple, fast(only needs about 3 min), cost effective, and sensitive for the detection of melamine in liquid milk samples. Therefore, it is more suitable for the field detection of melamine in liquid milk. Copyright © 2010 John Wiley & Sons, Ltd.     

Measurement and calculation of the Q‐branch spectrum of nitrogen using inverse Raman spectroscopy and cw Raman‐induced polarization spectroscopy

The techniques of inverse Raman spectroscopy, Raman‐induced polarization spectroscopy (RIPS), and optical heterodyne RIPS (OHD‐RIPS) are compared by probing the Q‐branch of the nitrogen molecule. The signal is measured employing either a photomultiplier tube (low background level–RIPS) or a photodetector (high background level–IRS and OHD‐RIPS). The measurements are performed using atmospheric mixtures of N₂ Ar with concentrations varying from 0 to 79% N₂. This strategy permits estimation of detection limits using the different techniques. Pump and probe energy levels are varied independently to study signal dependence on laser irradiance. A theoretical treatment is presented on the basis of the Raman susceptibility equations, which permits the calculation of spectra for all three techniques. Calculated Q‐branch spectra are compared with the measured spectra for the interactions of a linearly polarized probe beam with a linearly or circularly polarized pump beam. The polarizer angle in the detection path for OHD‐RIPS has a dramatic effect on the shape of the spectrum. The calculated and experimental OHD‐RIPS spectra are in good agreement over the entire range of investigated polarizer angles. Detection limits using these techniques are analyzed to suggest their applicability for measuring other species of importance in combustion and plasma systems. Copyright © 2007 John Wiley & Sons, Ltd.     

Experimental and statistical analysis methods for peptide detection using surface‐enhanced Raman spectroscopy

Surface‐enhanced Raman spectroscopy (SERS) has the potential to make a significant impact in biology research due to its ability to provide information orthogonal to that obtained by traditional techniques such as mass spectrometry (MS). While SERS has been well studied for its use in chemical applications, detailed investigations with biological molecules are less common. In addition, a clear understanding of how methodology and molecular characteristics impact the intensity, the number of peaks, and the signal‐to‐noise of SERS spectra is largely missing. By varying the concentration and order of addition of the SERS‐enhancer salt (LiCl) with colloidal silver, we were able to evaluate the impact of these variables on peptide spectra using a quantitative measure of spectra quality based on the number of peaks and peak intensity. The LiCl concentration and order of addition that produced the best SERS spectra were applied to a panel of synthetic peptides with a range of charges and isoelectric points (pIs) where the pI was directly correlated with higher spectral quality. Those peptides with moderate to high pIs and spectra quality scores were differentiated from each other using the improved method and a hierarchical clustering algorithm. In addition, the same method and algorithm was applied to a set of highly similar phosphorylated peptides, and it was possible to successfully classify the majority of peptides on the basis of species‐specific peak differences. Copyright © 2008 John Wiley & Sons, Ltd.     

Gold‐coated zinc oxide nanowire‐based substrate for surface‐enhanced Raman spectroscopy

Zinc oxide nanowires with two distinct morphologies were synthesized on silicon substrates using a simple thermal evaporation and vapor transport method in an oxidizing environment. The as‐synthesized nanowires were coated with gold to allow excitation of surface plasmons over a broad frequency range. SERS studies with near‐IR excitation at 785 nm showed significant enhancement (average enhancement > 10⁶) with excellent reproducibility to detect monolayer concentrations of 4‐methylbenzenethiol (4‐MBT) and 1,2‐benzendithiol (1,2‐BDT) probe molecules. The Raman enhancement showed a strong dependence on the gold film thickness, and the peak enhancement was observed for a ∼40‐nm‐thick film. The Raman enhancement was stronger for randomly oriented nanowires compared to aligned ones suggesting the importance of contributions from the junctions of nanowires. Copyright © 2009 John Wiley & Sons, Ltd.     

Near‐infrared Raman spectroscopy for gastric precancer diagnosis

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with neoplastic transformation. The purpose of this study was to apply near‐infrared (NIR) Raman spectroscopy for differentiating dysplasia from normal gastric mucosa tissue. A total of 65 gastric mucosa tissues (44 normal and 21 dysplasia) were obtained from 35 patients who underwent endoscopy investigation or gastrectomy operation for this study. A rapid NIR Raman system was utilized for tissue Raman spectroscopic measurements at 785‐nm laser excitation. High‐quality Raman spectra in the range of 800–1800 cm⁻¹ can be acquired from gastric mucosa tissue within 5 s. Raman spectra showed significant differences between normal and dysplastic tissue, particularly in the spectral ranges of 850–1150, 1200–1500 and 1600–1750 cm⁻¹, which contained signals related to proteins, nucleic acids and lipids. The diagnostic decision algorithm based on the combination of Raman peak intensity ratios of I₈₇₅/I₁₄₅₀ and I₁₂₀₈/I₁₆₅₅ and the logistic regression analysis yielded a diagnostic sensitivity of 90.5% and specificity of 90.9% for identification of gastric dysplasia tissue. This work demonstrates that NIR Raman spectroscopy in conjunction with intensity ratio algorithms has the potential for the noninvasive diagnosis and detection of precancer in the stomach at the molecular level. Copyright © 2009 John Wiley & Sons, Ltd.     

Plasmon‐enhanced polarized Raman spectroscopy for sensitive surface characterization

Local‐mode and localized surface plasmons generated on the silver thin film can selectively enhance the Raman signal from the surface. Further improvement of surface signal can be obtained by using the polarized Raman technique that results in a dramatic enhancement of the surface sensitivity by up to 25.4 times as compared to that without a silver coating. This technique will be very useful for Raman study on samples that suffer overlapping background signal. In this article, we show that it can be used to significantly improve the signal of thin strained‐Si layer on top of SiGe buffer layer. Copyright © 2008 John Wiley & Sons, Ltd.     

Automated detection and characterization of graphene and few‐layer graphite via Raman spectroscopy

Several processes have to be automated in order to use graphene in future industrial applications. One of these is the detection and characterization of graphene and few‐layer graphite (FLG) flakes on a substrate. Raman spectroscopy is an ideal tool for this purpose, as it allows not only the identification of these graphitic materials on arbitrary substrates but also monitoring the quality of flakes within the sample. In this paper, we report how graphene and FLG crystallites can be automatically detected and characterized by monitoring the evolution of Raman bands. We present an algorithm that achieves this purpose and thus has special potential in industrial applications of graphene. Copyright © 2010 John Wiley & Sons, Ltd.     

Two‐dimensional correlation Raman spectroscopy for characterizing protein structure and dynamics

Since the initial introduction of the basic concept almost twenty years ago, two‐dimensional correlation spectroscopy (2DCoS) has become a popular analytical tool applicable to a broad range of science problems. Vibrational spectroscopy remains the major area of 2DCoS applications where infrared spectroscopy is the most popular technique followed by Raman and Near Infrared spectroscopies. An increasing number of publications over the past few years have established Raman 2DCoS as a powerful problem solving technique in protein studies. In this review we provide a critical survey of recent protein studies using the 2DCoS Raman approach. We also analyze common misconceptions and potential pitfalls in the interpretation of 2D correlation data. Over the past decade, there have been a number of publications pointing to artifacts associated with visualization and interpretation of 2D correlation maps. We demonstrate here how some of the ‘artifacts’ of the 2DCoS approach in ‐ reality turn into the strength of the method. Copyright © 2009 John Wiley & Sons, Ltd.     

In‐situ Raman spectroscopy of current‐carrying graphene microbridge

In‐situ Raman spectroscopy was performed on chemical vapor deposited graphene microbridge (3 μm × 80 μm) under electrical current density up to 2.58 × 10⁸ A/cm² in ambient conditions. We found that both the G and the G′ peak of the Raman spectra do not restore back to the initial values at zero current, but to slightly higher values after switching off the current through the microbridge. The up‐shift of the G peak and the G′ peak, after switching off the electrical current, is believed to be due to p‐doping by oxygen adsorption, which is confirmed by scanning photoemission microscopy. Both C–O and C=O bond components in the C1s spectra from the microbridge were found to be significantly increased after high electrical current density was flown. The C=O bond is likely the main source of the p‐doping according to our density functional theory calculation of the electronic structure. Copyright © 2014 John Wiley & Sons, Ltd.     

Simple and inexpensive instrument for deep‐UV Raman spectroscopy

Deep‐UV Raman spectroscopy is a powerful way to collect chemically specific information about complex samples. The availability of inexpensive and reliable light sources in the spectral region below 250 nm has been always considered a major bottleneck problem on the way of a widespread of this powerful spectroscopic technique. We report on the efficient fourth‐harmonic generation of a low‐power microchip Nd:YAG laser operating at 946 nm. High‐quality deep‐UV Raman spectra were collected using a newly developed laser source. Copyright © 2013 John Wiley & Sons, Ltd.     

Silica‐overcoated substrates for detection of proteins by surface‐enhanced Raman spectroscopy

Ag film over nanosphere (AgFON) substrates for surface‐enhanced Raman spectroscopy (SERS) are shown to be ineffective for the detection of proteins in phosphate buffer solution (PBS) because of the decomposition of the substrate resulting in a total loss of SERS activity. However, modification of these substrates with SiO₂ overlayers overcomes this problem. The SiO₂ overlayers are produced by filtered arc deposition (FAD) and are characterised by atomic force microscopy (AFM). Their porosity is examined using Raman spectroscopy and the detection of cytochrome c and bovine serum albumin in PBS is successfully demonstrated. These findings show promise for the detection of proteins in biologically relevant conditions using Ag‐based SERS substrates. Copyright © 2008 John Wiley & Sons, Ltd.     

Polarized Raman spectroscopy for enhanced quantification of protein concentrations in an aqueous mixture

Raman spectroscopy (RS) for selective quantification of protein species in mixed solutions holds enormous potential for advancing protein detection technology to significantly faster, cheaper, and less technically demanding platforms. However, even with powerful computational methods such as nonlinear least squares regression, protein quantification in such complex systems suffers from relatively poor accuracy, especially in comparison with established methods. In this work, a combination of the expanded set of spectral information provided by polarized Raman spectroscopy (PRS) that is otherwise unavailable in conventional RS was, to our knowledge, explored to enhance the quantitative accuracy and robustness of protein quantification for the first time. A mixture containing two proteins, lysozyme and α‐amylase, was used as a model system to demonstrate enhanced quantitative accuracy and robustness of selective protein quantification using PRS. The concentrations of lysozyme and α‐amylase in mixtures were estimated using data obtained from both traditional RS and PRS. A new method was developed to select highly sensitive peaks for accurate concentration estimation to take advantage of additional spectra offered by PRS. The root‐mean squared errors (RMSE) of estimation using traditional RS and PRS were compared. A drastic improvement in RMSE was observed from traditional RS to PRS, where the RMSEs of α‐amylase and lysozyme concentrations decreased by 11 and 7 times, respectively. Therefore, this technique is a successful demonstration in achieving greater accuracy and reproducibility in the estimation of protein concentration in a mixture, and it could play a significant role in future multiplexed protein quantification platforms. Copyright © 2015 John Wiley & Sons, Ltd.