Parasites under the Spotlight: Applications of Vibrational Spectroscopy to Malaria Research

Tracking heme biology with resonance Raman spectroscopy

Heme proteins are a large group of biomolecules with heme incorporated as a prosthetic group. Apart from cytochromes present in almost all cell types, many other specific heme proteins are expressed in different kinds of cells, e.g. hemoglobin in the erythrocytes, myoglobin (skeletal and vascular smooth muscle cells), cytoglobin (fibroblasts) and neuroglobin (neurons and retina). Among their wide and diverse biological functions, the most important is their unique ability to bind, store, and transport gaseous molecules, such as oxygen, carbon monoxide, and nitric oxide. Resonance Raman (RR) spectroscopy is an exceptional analytical tool that allows for qualitative and quantitative characterization of heme proteins in biological systems. Due to its high sensitivity, even subtle structural alterations of the heme group can be monitored and tracked during cellular processes. Resonance Raman excitation within the Soret absorption band (390-440 nm) provides rich information on the environment of heme's active site, allowing differentiation of the iron ion oxidation and spin states, and tracking the movement of the porphyrin ring plane in response to the changes in oxygenation status. Herein, we summarize and discuss recent developments in RR applications aimed to link the structure-function relationship of heme proteins within biological systems, connected, e.g., with the formation of hemoglobin (Hb) adducts (nitrosylhemoglobin, cyanhemoglobin, sulfhemoglobin), irreversible Hb alterations deteriorating oxygen binding and differentiation of heme proteins oxidation state within live cells in situ.

Quantification and profiling of urine cells by integrated cytocentrifugation and infrared spectroscopy

The presence of cells in urine and in particular White Blood Cells (WBCs) is often associated with Urinary Tract Infections (UTIs) and other diseases. Non-invasive screening of WBCs requires the development of cost-effective point of care diagnostic tools. Infrared (IR) spectroscopy has the potential to identify and quantify cells in urine. However, the quantification of cells by compact IR spectrophotometers can be hindered by the presence of highly concentrated interfering biomolecules. The use of separation procedures can assist in identifying and quantifying cells but reduces the point of care capabilities of the technology. In this study, we propose coupling cytocentrifugation with transflection IR spectroscopy for the isolation and quantification of cells in urine. Urine samples were spiked with monocytes and T-lymphocytes, cyto-centrifuged onto low-e slides and measured in transflection mode. An optional cell clean-up step, either performed before (by resuspending in PBS) or after the cytocentrifugation (by soaking the slide in water), was evaluated. In a first experiment using monocytes, IR band areas were linear (R2 = 0.98) in the 8 × 103-2 × 105 cells mL-1 range, thus demonstrating the detection of cells at pathological numbers (pyuria, i.e., >104 WBCs mL-1). Secondly, to mimic real samples with varying cell types, urine samples containing both monocytes and T-lymphocytes were analysed to determine their concentration simultaneously. Partial Least Squares (PLS) regression enabled the simultaneous quantification of two types of different cells, yielding prediction errors of 2 × 104 cells mL-1 for monocytes and 4 × 104 cells mL-1 for T-lymphocytes. The results suggest that the technique has the potential to be implemented as a fast, simple, versatile, and cost-effective method for quantifying and profiling cells in urine.

Synchrotron-Infrared Microspectroscopy of Live Leishmania major Infected Macrophages and Isolated Promastigotes and Amastigotes

The prevalence of neglected tropical diseases (NTDs) is advancing at an alarming rate. The NTD leishmaniasis is now endemic in over 90 tropical and sub-tropical low socioeconomic countries. Current diagnosis for this disease involves serological assessment of infected tissue by either light microscopy, antibody tests, or culturing with in vitro or in vivo animal inoculation. Furthermore, co-infection by other pathogens can make it difficult to accurately determine Leishmania infection with light microscopy. Herein, for the first time, we demonstrate the potential of combining synchrotron Fourier-transform infrared (FTIR) microspectroscopy with powerful discrimination tools, such as partial least squares-discriminant analysis (PLS-DA), support vector machine-discriminant analysis (SVM-DA), and k-nearest neighbors (KNN), to characterize the parasitic forms of Leishmania major both isolated and within infected macrophages. For measurements performed on functional infected and uninfected macrophages in physiological solutions, the sensitivities from PLS-DA, SVM-DA, and KNN classification methods were found to be 0.923, 0.981, and 0.989, while the specificities were 0.897, 1.00, and 0.975, respectively. Cross-validated PLS-DA models on live amastigotes and promastigotes showed a sensitivity and specificity of 0.98 in the lipid region, while a specificity and sensitivity of 1.00 was achieved in the fingerprint region. The study demonstrates the potential of the FTIR technique to identify unique diagnostic bands and utilize them to generate machine learning models to predict Leishmania infection. For the first time, we examine the potential of infrared spectroscopy to study the molecular structure of parasitic forms in their native aqueous functional state, laying the groundwork for future clinical studies using more portable devices.

Label-free testing strategy to evaluate packed red blood cell quality before transfusion to leukemia patients

Patients worldwide require therapeutic transfusions of packed red blood cells (pRBCs), which is applied to the high-risk patients who need periodic transfusions due to leukemia, lymphoma, myeloma and other blood diseases or disorders. Contrary to the general hospital population where the transfusions are carried out mainly for healthy trauma patients, in case of high-risk patients the proper quality of pRBCs is crucial. This leads to an increased demand for efficient technology providing information on the pRBCs alterations deteriorating their quality. Here we present the design of an innovative, label-free, noninvasive, rapid Raman spectroscopy-based method for pRBCs quality evaluation, starting with the description of sample measurement and data analysis, through correlation of spectroscopic results with reference techniques' outcomes, and finishing with methodology verification and its application in clinical conditions. We have shown that Raman spectra collected from the pRBCs supernatant mixture with a proper chemometric analysis conducted for a minimum one ratio of integral intensities of the chosen Raman marker bands within the spectrum allow evaluation of the pRBC quality in a rapid, noninvasive, and free-label manner, without unsealing the pRBCs bag. Subsequently, spectroscopic data were compared with predefined reference values, either from pRBCs expiration or those defining the pRBCs quality, allowing to assess their utility for transfusion to patients with acute myeloid leukemia (AML) and lymphoblastic leukemia (ALL).

Discriminant Analysis PCA-LDA Assisted Surface-Enhanced Raman Spectroscopy for Direct Identification of Malaria-Infected Red Blood Cells

Various methods for detecting malaria have been developed in recent years, each with its own set of advantages. These methods include microscopic, antigen-based, and molecular-based analysis of blood samples. This study aimed to develop a new, alternative procedure for clinical use by using a large data set of surface-enhanced Raman spectra to distinguish normal and infected red blood cells. PCA-LDA algorithms were used to produce models for separating P. falciparum (3D7)-infected red blood cells and normal red blood cells based on their Raman spectra. Both average normalized spectra and spectral imaging were considered. However, these initial spectra could hardly differentiate normal cells from the infected cells. Then, discrimination analysis was applied to assist in the classification and visualization of the different spectral data sets. The results showed a clear separation in the PCA-LDA coordinate. A blind test was also carried out to evaluate the efficiency of the PCA-LDA separation model and achieved a prediction accuracy of up to 80%. Considering that the PCA-LDA separation accuracy will improve when a larger set of training data is incorporated into the existing database, the proposed method could be highly effective for the identification of malaria-infected red blood cells.

Clinical Spectroscopy: Lost in Translation?

This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.

Visible microspectrophotometry coupled with machine learning to discriminate the erythrocytic life cycle stages of P. falciparum malaria parasites in functional single cells

Visible microspectroscopy combined with machine learning is able to detect and quantify functional malaria infected erythrocytes at different stages of the P. falciparum erythrocytic life cycle.

Multiplexed Fourier Transform Infrared and Raman Imaging

Infrared (IR) and Raman spectroscopies are being increasingly employed for the label-free analysis of biochemical samples. Both are vibrational imaging techniques, but they provide complementary information about the chemical composition of the sample, and thus the integration of Raman and IR images leads to a comprehensive understanding of the samples. Here, we summarize the steps needed for performing multiplexed infrared and Raman imaging, identifying and overcoming the two main challenges: first, the technical difficulties caused by the incompatibilities of the techniques and, second, the necessity to extract the information from the large number of vibrational variables found in both IR and Raman spectra.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

A Near-Infrared "Matchbox Size" Spectrometer to Detect and Quantify Malaria Parasitemia

New point-of-care diagnostic approaches for malaria that are sensitive to low parasitemia, easy to use in a field setting, and affordable are urgently required to meet the World Health Organization's objective of reducing malaria cases and related life losses by 90% globally on or before 2030. In this study, an inexpensive "matchbox size" near-infrared (NIR) spectrophotometer was used for the first time to detect and quantify malaria infection in vitro from isolated dried red blood cells using a fingerpick volume of blood. This the first study to apply a miniaturized NIR device to diagnose a parasitic infection and identify marker bands indicative of malaria infection in the NIR region. An NIR device has many advantages including wavelength accuracy and repeatability, speed, resolution, and a greatly improved signal-to-noise ratio compared to existing spectroscopic options. Using multivariate data analysis, we discriminated control red blood cells from infected cells and established the limit of detection of the technique. Principal component analysis displayed a good separation between the infected and uninfected RBCs, while partial least-squares regression analysis yielded a robust parasitemia prediction with root-mean-square error of prediction values of 0.446 and 0.001% for the higher and lower parasitemia models, respectively. The R² values of the higher and lower parasitemia models were 0.947 and 0.931, respectively. Finally, an estimated parasitemia detection limit of 0.00001% and a qunatification limit of 0.001% was achieved; to ascertain the true efficacy of the technique for point-of-care screening, clinical studies using large patient numbers are required, which is the subject of future studies.

Understanding the structural insights of enzymatic conformations for adenylosuccinate lyase receptor in malarial parasite Plasmodium falciparum

The dreadful disease malaria is one among the infectious diseases that comes in third number after the tuberculosis and HIV. This disease is spread by female Anopheles mosquito and caused by the malarial parasite sp notably Plasmodium falciparum. In this, the organism has several enzymes for processing the infection and growth mechanism and among that, the adenylosuccinate lyase is an enzyme that plays a critical role in metabolism and cellular replication via its action in the de novo purine biosynthetic pathway. Adenylosuccinate has been studied for two reaction mechanisms, and in that, the adenylosuccinate to AMP and fumarate is core important. As of now, there have been several studies indicating the reaction mechanism of adenylosuccinate lyase, this study projects the conformations of the reactant and product changes through molecular docking and molecular dynamic simulations. Adenylosuccinate bound complex involves His role in the product than the reactant complex, and the complex shows high flexibility due to fumarate. Thus, identifying the core inhibitor that binds to His rings could be a standard adenylosuccinate lyase inhibitor, that can block the malarial diseases in humans. In addition to the competitive inhibition site, we also predicted the uncompetitive ligand binding site, which suggest the alternate region to be targeted. Thus, from this work, we suggest both competitive and uncompetitive binding regions for the purpose identifying the malarial inhibitors.

Probing the structure-function relationship of hemoglobin in living human red blood cells

Hemoglobin (Hb) is a key component of respiratory system and as such plays important role in human physiology. The studies of Hb's structure and functions are usually performed on cell-free protein; however, it has been shown that there are functionally relevant differences between isolated Hb and Hb present inside red blood cells (RBCs). It is clear that new experimental approaches are needed to understand the origin of these differences and to gain insight into the structure-function relationship of Hb within intact living cells. In this work we present a novel application of Resonance Raman spectroscopy to study heme active site of different forms of human Hb within living RBCs using laser excitation lines in resonance with their Soret absorption bands. These studies revealed that there are no significant changes in the disposition of the Fe-O-O fragment or the Fe-N_His linkage for Hb molecules enclosed in RBCs and these in free isolated states. However, some changes in the orientation of the heme vinyl groups were observed which might account for the differences in the protein activity and ligand affinity. This work highlights importance of protein-based studies and presents a new opportunity to translate these results to physiological cell systems.

Irreversible alterations in the hemoglobin structure affect oxygen binding in human packed red blood cells

The ability of hemoglobin (Hb) to transport respiratory gases is directly linked to its quaternary structure properties and reversible changes between T (tense) and R (relax) state. In this study we demonstrated that packed red blood cells (pRBCs) storage resulted in a gradual increase in the irreversible changes in the secondary and quaternary structures of Hb, with subsequent impairment of the T↔R transition. Such alteration was associated with the presence of irreversibly settled in the relaxed form, quaternary structure of Hb, which we termed R'. On the secondary structure level, disordered protein organization involved formation of β-sheets and a decrease in α-helices related to the aggregation process stabilized by strong intermolecular hydrogen bonding. Compensatory changes in RBCs metabolism launched to preserve reductive microenvironment were disclosed as an activation of nicotinamide adenine dinucleotide phosphate (NADPH) production and increased reduced to oxidized glutathione (GSH/GSSG) ratio. For the first time we showed the relationship between secondary structure changes and the occurrence of newly discovered R', which through an artificial increase in oxyhemoglobin level altered Hb ability to bind and release oxygen.

Postmortem Diagnosis of Fatal Hypothermia by Fourier Transform Infrared Spectroscopic Analysis of Edema Fluid in Formalin-Fixed, Paraffin-Embedded Lung Tissues

The goal of this study was to investigate whether pulmonary edema could become a specific diagnostic marker for fatal hypothermia using Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics. The spectral profile analysis indicated that hypothermia fatalities associated with pulmonary edema fluid contained more β-sheet protein conformational structures than the control causes of death, which included sudden cardiac death, brain injury, cerebrovascular disease, mechanical asphyxiation, intoxication, and drowning. Subsequently, the results of principal component analysis (PCA) further revealed that the content of β-sheet protein conformational structures in the pulmonary edema fluid was the main discriminatory marker between fatal hypothermia and the other causes of death. Ultimately, a robust postmortem diagnostic model for fatal hypothermia using a partial least-squares discriminant analysis (PLS-DA) algorithm was constructed. Pulmonary edema fluid spectra collected from eight new forensic autopsy cases that did not participate in the construction of the diagnostic model were predicted using the model. The results showed the causes of death of all these eight cases were correctly classified. In conclusion, this preliminary study demonstrates that FTIR spectroscopy in combination with chemometrics could be a promising approach for the postmortem diagnosis of fatal hypothermia.

Determination of causes of death via spectrochemical analysis of forensic autopsies-based pulmonary edema fluid samples with deep learning algorithm

This study investigated whether infrared spectroscopy combined with a deep learning algorithm could be a useful tool for determining causes of death by analyzing pulmonary edema fluid from forensic autopsies. A newly designed convolutional neural network-based deep learning framework, named DeepIR and eight popular machine learning algorithms, were used to construct classifiers. The prediction performances of these classifiers demonstrated that DeepIR outperformed the machine learning algorithms in establishing classifiers to determine the causes of death. Moreover, DeepIR was generally less dependent on preprocessing procedures than were the machine learning algorithms; it provided the validation accuracy with a narrow range from 0.9661 to 0.9856 and the test accuracy ranging from 0.8774 to 0.9167 on the raw pulmonary edema fluid spectral dataset and the nine preprocessing protocol-based datasets in our study. In conclusion, this study demonstrates that the deep learning-equipped Fourier transform infrared spectroscopy technique has the potential to be an effective aid for determining causes of death.

Multimodal detection and analysis of a new type of advanced Heinz body-like aggregate (AHBA) and cytoskeleton deformation in human RBCs

A new type of aggregate, formed in human red blood cells (RBCs) in response to glutaraldehyde treatment, was discovered and analyzed with the classical and advanced biomolecular imaging techniques. Advanced Heinz body-like aggregates (AHBA) formed in a single human RBC are characterized by a higher level of hemoglobin (Hb) degradation compared to typical Heinz bodies, which consist of hemichromes. The complete destruction of the porphyrin structure of Hb and the aggregation of the degraded proteins in the presence of Fe³⁺ ions are observed. The presence of such aggregated, highly degraded proteins inside RBCs, without cell membrane destruction, has been never reported before. For the first time the spatial differentiation of two kinds of protein mixtures inside a single RBC, with different phenylalanine (Phe) conformations, is visualized. The non-resonant Raman spectra of altered RBCs with AHBA are characterized by the presence of a strong band located at 1037 cm^-1, which confirms that glutaraldehyde interacts strongly with Phe. The shape-shifting of RBCs from a biconcave disk to a spherical structure and sinking of AHBA to the bottom of the cell are observed. Results reveal that the presence of AHBA should be considered when fixing RBCs and indicate the analytical potential of Raman spectroscopy, atomic force microscopy and scanning near-field optical microscopy in AHBA detection and analysis.

Comparison of standard and HD FT-IR with multimodal CARS/TPEF/SHG/FLIMS imaging in the detection of the early stage of pulmonary metastasis of murine breast cancer

The comparison of the potential of FT-IR in standard and high definition modes with multimodal CARS/TPEF/SHG/FLIMS imaging for detection of the early stage of pulmonary metastasis of murine breast cancer is presented.

Infrared spectroscopy coupled to cloud-based data management as a tool to diagnose malaria: a pilot study in a malaria-endemic country

Background

Widespread elimination of malaria requires an ultra-sensitive detection method that can detect low parasitaemia levels seen in asymptomatic carriers who act as reservoirs for further transmission of the disease, but is inexpensive and easy to deploy in the field in low income settings. It was hypothesized that a new method of malaria detection based on infrared spectroscopy, shown in the laboratory to have similar sensitivity to PCR based detection, could prove effective in detecting malaria in a field setting using cheap portable units with data management systems allowing them to be used by users inexpert in spectroscopy. This study was designed to determine whether the methodology developed in the laboratory could be translated to the field to diagnose the presence of Plasmodium in the blood of patients presenting at hospital with symptoms of malaria, as a precursor to trials testing the sensitivity of to detect asymptomatic carriers.

Methods

The field study tested 318 patients presenting with suspected malaria at four regional clinics in Thailand. Two portable infrared spectrometers were employed, operated from a laptop computer or a mobile telephone with in-built software that guided the user through the simple measurement steps. Diagnostic modelling and validation testing using linear and machine learning approaches was performed against the gold standard qPCR. Sample spectra from 318 patients were used for building calibration models (112 positive and 110 negative samples according to PCR testing) and independent validation testing (39 positive and 57 negatives samples by PCR).

Results

The machine learning classification (support vector machines; SVM) performed with 92% sensitivity (3 false negatives) and 97% specificity (2 false positives). The Area Under the Receiver Operation Curve (AUROC) for the SVM classification was 0.98. These results may be better than as stated as one of the spectroscopy false positives was infected by a Plasmodium species other than Plasmodium falciparum or Plasmodium vivax, not detected by the PCR primers employed.

Conclusions

In conclusion, it was demonstrated that ATR-FTIR spectroscopy could be used as an efficient and reliable malaria diagnostic tool and has the potential to be developed for use at point of care under tropical field conditions with spectra able to be analysed via a Cloud-based system, and the diagnostic results returned to the user’s mobile telephone or computer. The combination of accessibility to mass screening, high sensitivity and selectivity, low logistics requirements and portability, makes this new approach a potentially outstanding tool in the context of malaria elimination programmes. The next step in the experimental programme now underway is to reduce the sample requirements to fingerprick volumes.

Is Infrared Spectroscopy Ready for the Clinic?

Fourier transform-infrared spectroscopy (FT-IR) represents an attractive molecular diagnostic modality for translation to the clinic, where comprehensive chemical profiling of biological samples may revolutionize a myriad of pathways in clinical settings. Principally, FT-IR provides a rapid, cost-effective platform to obtain a molecular fingerprint of clinical samples based on vibrational transitions of chemical bonds upon interaction with infrared light. To date, considerable research activities have demonstrated competitive to superior performance of FT-IR strategies in comparison to conventional techniques, with particular promise for earlier, accessible disease diagnostics, thereby improving patient outcomes. However, amidst the changing healthcare landscape in times of aging populations and increased prevalence of cancer and chronic disease, routine adoption of FT-IR within clinical laboratories has remained elusive. Hence, this perspective shall outline the significant clinical potential of FT-IR diagnostics and subsequently address current barriers to translation from the perspective of all stakeholders, in the context of biofluid, histopathology, cytology, microbiology, and biomarker discovery frameworks. Thereafter, future perspectives of FT-IR for healthcare will be discussed, with consideration of recent technological advances that may facilitate future clinical translation.

In-Situ Infrared Spectroscopy Applied to the Study of the Electrocatalytic Reduction of CO2 : Theory, Practice and Challenges

The field of electrochemical CO₂ conversion is undergoing significant growth in terms of the number of publications and worldwide research groups involved. Despite improvements of the catalytic performance, the complex reaction mechanisms and solution chemistry of CO₂ have resulted in a considerable amount of discrepancies between theoretical and experimental studies. A clear identification of the reaction mechanism and the catalytic sites are of key importance in order to allow for a qualitative breakthrough and, from an experimental perspective, calls for the use of in-situ or operando spectroscopic techniques. In-situ infrared spectroscopy can provide information on the nature of intermediate species and products in real time and, in some cases, with relatively high time resolution. In this contribution, we review key theoretical aspects of infrared reflection spectroscopy, followed by considerations of practical implementation. Finally, recent applications to the electrocatalytic reduction of CO₂ are reviewed, including challenges associated with the detection of reaction intermediates.

Whole-Organism Analysis by Vibrational Spectroscopy

Vibrational spectroscopy has contributed to the understanding of biological materials for many years. As the technology has advanced, the technique has been brought to bear on the analysis of whole organisms. Here, we discuss advanced and recently developed infrared and Raman spectroscopic instrumentation to whole-organism analysis. We highlight many of the recent contributions made in this relatively new area of spectroscopy, particularly addressing organisms associated with disease with emphasis on diagnosis and treatment. The application of vibrational spectroscopic techniques to entire organisms is still in its infancy, but new developments in imaging and chemometric processing will likely expand in the field in the near future.

Synchrotron macro ATR-FTIR microspectroscopy for high-resolution chemical mapping of single cells

Coupling synchrotron IR beam to an ATR element enhances spatial resolution suited for high-resolution single cell analysis in biology, medicine and environmental science.

Challenges in application of Raman spectroscopy to biology and materials

Raman spectroscopy has become an essential tool for chemists, physicists, biologists and materials scientists. In this article, we present the challenges in unravelling the molecule-specific Raman spectral signatures of different biomolecules like proteins, nucleic acids, lipids and carbohydrates based on the review of our work and the current trends in these areas. We also show how Raman spectroscopy can be used to probe the secondary and tertiary structural changes occurring during thermal denaturation of protein and lysozyme as well as more complex biological systems like bacteria. Complex biological systems like tissues, cells, blood serum etc. are also made up of such biomolecules. Using mice liver and blood serum, it is shown that different tissues yield their unique signature Raman spectra, owing to a difference in the relative composition of the biomolecules. Additionally, recent progress in Raman spectroscopy for diagnosing a multitude of diseases ranging from cancer to infection is also presented. The second part of this article focuses on applications of Raman spectroscopy to materials. As a first example, Raman spectroscopy of a melt cast explosives formulation was carried out to monitor the changes in the peaks which indicates the potential of this technique for remote process monitoring. The second example presents various modern methods of Raman spectroscopy such as spatially offset Raman spectroscopy (SORS), reflection, transmission and universal multiple angle Raman spectroscopy (UMARS) to study layered materials. Studies on chemicals/layered materials hidden in non-metallic containers using the above variants are presented. Using suitable examples, it is shown how a specific excitation or collection geometry can yield different information about the location of materials. Additionally, it is shown that UMARS imaging can also be used as an effective tool to obtain layer specific information of materials located at depths beyond a few centimeters.

This paper reviews various facets of Raman spectroscopy. This encompasses biomolecule fingerprinting and conformational analysis, discrimination of healthy vs. diseased states, depth-specific information of materials and 3D Raman imaging.