Micro-Raman spectroscopy study of optically trapped erythrocytes in malaria, dengue and leptospirosis infections.

Malaria, dengue and leptospirosis are three tropical infectious diseases that present with severe hematological derangement causing significant morbidity and mortality, especially during the seasonal monsoons. During the course of these infectious diseases, circulating red blood cells are imperiled to the direct ill-effects of the infectious pathogen in the body as well as to the pro-inflammatory cytokines generated as a consequence of the infection. RBCs when exposed to such inflammatory and/or pathogenic milieu are susceptible to injuries such as RBC programmed or RBC programmed .

Micro-Raman Spectroscopy Analysis of Optically Trapped Erythrocytes in Jaundice.

Derangements in bilirubin metabolism and/or dysfunctions in the hepato-biliary system lead to the unhealthy buildup of bilirubin in blood, resulting in jaundice. During the course of this disorder, circulating red cells are invariably subjected to toxic effects of serum bilirubin and an array of inflammatory compounds. This study aimed to investigate the vibrational spectroscopy of live red cells in jaundice using micro-Raman spectroscopy combined with optical-trap.

Influence of static electric field on Raman polarizability of optically trapped polystyrene beads.

The influence of static electric field of about 4.9 kV/cm on optically trapped polystyrene bead has been studied using micro-Raman spectroscopy. This experimental method could explore the response of electronic polarizability of molecules to the static electric field by measuring the Raman intensity.

A micro-Raman and chemometric study of urinary tract infection-causing bacterial pathogens in mixed cultures.

Detection of urinary tract infection (UTI)-causing bacteria uses conventional time-consuming microbiological techniques. The current need is to use a fast and reliable method of bacterial identification. In order to unambiguously distinguish the UTI-causing five bacterial species used in the current study, micro-Raman spectra were obtained from a home-assembled micro-Raman system and analyzed by multivariate statistical techniques such as principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and support vector machine (SVM).