Characterization of three different benzimidazolium ligands and their organo-selenium complexes by using density functional theory and Raman spectroscopy.

In the present study, Raman spectroscopy (RS) along with density functional theory (DFT) calculations have been performed for the successful characterization and confirmation of the formation of three different selenium-based N-heterocyclic carbene (NHC) complexes from their respective salts. For this purpose, mean RS features and DFT calculations of different ligands and their respective selenium NHC complexes are compared. The identified characteristic RS and DFT features, of each of these ligands and their selenium complexes, show that the polarizability of benzimidazolium rings increases after complex formation with selenium. This has been shown by the enhanced intensity of the associated Raman peaks, therefore, confirming the formation of newly formed bonds. The complex formation is also confirmed by the identification of several new peaks in the spectra of complexes and these Raman bands were absent in the spectra of the ligands. Moreover, Raman spectral data sets are analyzed using a multivariate data analysis technique of Principal Component Analysis (PCA) to observe the efficiency of the RS analysis. The results presented in this study have proved the RS technique, along with DFT, an undoubtedly fast approach for the confirmation of synthesis of selenium based NHC-complexes.

Surface-enhanced Raman spectroscopy of polymerase chain reaction (PCR) products of Rifampin resistant and susceptible tuberculosis patients.

BACKGROUND: Raman spectroscopy is an effective tool for detecting and discriminating microorganisms that is robust, reliable, and rapid. OBJECTIVES: To develop a polymerase chain reaction technique (PCR) based on Surface Enhanced Raman Spectroscopy (SERS) technique with principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to assess diagnostic capability of SERS for distinguishing between tuberculosis (TB) positive rifampin resistant and tuberculosis (TB) positive rifampin susceptible samples. METHODS: Silver nanoparticles (Ag NPs) were used as SERS substrates and technique was used to distinguish TB positive rifampin (RIF) resistant and TB positive rifampin (RIF) susceptible patients on the basis of characteristic SERS spectral features of their respective PCR products. SERS spectra were acquired from 52 samples of PCR products including 22 samples of TB positive rifampin susceptible, 30 samples of TB positive rifampin resistant and negative control samples. All these samples were collected from individuals of same age. Furthermore, multivariate data analyses techniques such as PCA and PLS-DA were used to assess diagnostic capability of SERS for distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples. RESULTS: PCA is found helpful for successful differentiation among these two groups of spectral data sets. Moreover, PLS-DA provides this classification quantitatively by predicting the class of SERS spectral data set with 73% area under curve, 96% sensitivity, 95.6% specificity and 95% accuracy. CONCLUSION: SERS can be employed for the rapid distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples.