Raman and Infrared (IR) spectroscopies provide information about the structure, functional groups and environment of the molecules in the sample. In combination with a microscope, these techniques can also be used to study molecular distributions in heterogeneous samples. Over the past few decades Raman and IR microspectroscopy based techniques have been extensively used to understand fundamental biology and responses of living systems under diverse physiological and pathological conditions. The spectra from biological systems are complex and diverse, owing to their heterogeneous nature consisting of bio-molecules such as proteins, lipids, nucleic acids, carbohydrates etc. Sometimes minor differences may contain critical information. Therefore, interpretation of the results obtained from Raman and IR spectroscopy is difficult and to overcome these intricacies and for deeper insight we need to employ various data mining methods. These methods must be suitable for handling large multidimensional data sets and for exploring the complete spectral information simultaneously. The effective implementation of these multivariate data analysis methods requires the pretreatment of data. The preprocessing of raw data helps in the elimination of noise (unwanted signals) and the enhancement of discriminating features. This review provides an outline of the state-of-the-art data processing tools for multivariate analysis and the various preprocessing methods that are widely used in Raman and IR spectroscopy including imaging for better qualitative and quantitative analysis of biological samples.

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.

We demonstrate how ratioing spectral bands can circumvent experimental artefacts, and present a library of ratios from the biomedical literature.

Breast cancer is the most prevalent cause of cancer-associated death in women the world over, but if detected early it can be treated successfully. Therefore, it is important to diagnose this disease at an early stage and to understand the biochemical changes associated with cellular transformation and cancer progression. Deregulated lipid metabolism has been shown to contribute to cell transformation as well as cancer progression. In this study, we monitored the biomolecular changes associated with the transformation of a normal cell into an invasive cell associated with breast cancer using Raman microspectroscopy. We have utilized primary normal breast cells, and immortalized, transformed, non-invasive, and invasive breast cancer cells. The Raman spectra were acquired from all these cell lines under physiological conditions. The higher wavenumber (2800–3000 cm⁻¹) and lower wavenumber (700–1800 cm⁻¹) range of the Raman spectrum were analyzed and we observed increased lipid levels for invasive cells. The Raman spectral data were analyzed by principal component–linear discriminant analysis (PC-LDA), which resulted in the formation of distinct clusters for different cell types with a high degree of sensitivity. The subsequent testing of the PC-LDA analysis via the leave-one-out cross validation approach (LOOCV) yielded relatively high identification sensitivity. Additionally, the Raman spectroscopic results were confirmed through fluorescence staining tests with BODIPY and Nile Red biochemical assays. Furthermore, Raman maps from the above mentioned cells under fixed conditions were also acquired to visualize the distribution of biomolecules throughout the cell. The present study shows the suitability of Raman spectroscopy as a non-invasive, label-free, microspectroscopic technique, having the potential of probing changes in the biomolecular composition of living cells as well as fixed cells.

We demonstrate observation of Raman signals of different analytes adsorbed on carbonaceous materials, such as, chemically reduced graphene, graphene oxide (GO), multi-walled carbon nanotube (MWCNT), graphite and activated carbon. The analytes selected for the study were Rhodamine 6G (R6G) (in resonant conditions), Rhodamine B (RB), Nile blue (NBA), Crystal Violet (CV) and acetaminophen (paracetamol). All the analytes except paracetamol absorb and fluoresce in the visible region. In this article we provide experimental evidence of the fact that observation of Raman signals of analytes on such carbonaceous materials are more due to resonance effect, suppression of fluorescence and efficient adsorption and that this property in not unique to graphene or nanotubes but prevalent for various type of carbon materials.