Monitoring neurotransmitter release using surface-enhanced Raman spectroscopy.

Surface-enhanced Raman spectroscopy (SERS) is a promising tool to monitor neurotransmitter release at the single-cell level: it is a sensitive technique that provides structural information of the released compounds and spatial information about their release sites. In this study we demonstrate that depolarization-evoked catecholamine secretion by rat phaeochromocytoma (PC12) cells can be spatially resolved by SERS using silver colloids. A suitable SERS substrate was created by adding silver colloids to the cell culture medium. Nomarski-DIC microscopy combined with reflection confocal laser scanning microscopy showed that the colloids were primarily present on top of the cell membrane. The SERS spectra were successfully corrected for the contribution of cell constituents. Dopamine and noradrenaline were localized by examining the correlation coefficient between spectra and reference catecholamine spectra. Potential improvements of the temporal resolution of the technique are discussed.

New background correction method for liquid chromatography with diode array detection, infrared spectroscopic detection and Raman spectroscopic detection.

A new method to eliminate the background spectrum (EBS) during analyte elution in column liquid chromatography (LC) coupled to spectroscopic techniques is proposed. This method takes into account the shape and also intensity differences of the background eluent spectrum. This allows the EBS method to make a better estimation of the background eluent spectrum during analyte elution. This is an advantage for quantification as well as for identification of analytes. The EBS method uses a two-step procedure. First, the baseline spectra are modeled using a limited number of principal components (PCs). Subsequently, an asymmetric least squares (asLS) regression method is applied using these principal components to correct the measured spectra during elution for the background contribution. The asymmetric least squares regression needs one parameter, the asymmetry factor p. This asymmetry factor determines relative weight of positive and negative residuals. Simulations are performed to test the EBS method in well-defined situations. The effect of spectral noise on the performance and the sensitivity of the EBS method for the value of the asymmetry factorp is tested. Two applications of the EBS method are discussed. In the first application, the goal is to extract the analyte spectrum from an LC-Raman analysis. In this case, the EBS method facilitates easy identification of unknown analytes using spectral libraries. In a second application, the EBS method is used for baseline correction in LC-diode array detection (DAD) analysis of polymeric standards during a gradient elution separation. It is shown that the EBS method yields a good baseline correction, without the need to perform a blank chromatographic run.

Capillary electrophoresis coupled on-line with ultraviolet resonance Raman spectroscopy.

Capillary electrophoresis (CE) and resonance Raman spectroscopy (RRS) with excitation in the deep ultraviolet (UV) region (lambda(ex): 244 or 257 nm) were coupled on-line. The potential of this hyphenated technique, denoted as CE-UV-RRS, for analyte confirmation/identification purposes was explored with aromatic sulfonic acids and nucleotides as test compounds. Good-quality UV-RRS spectra could be recorded on-the-fly. Identification limits for the nucleotides were in the 10-125 microg/mL range. The RRS spectra showed sufficient characteristic features to enable analyte confirmation. In addition, the identification power of UV-RRS was studied with substituted pyrenes as model compounds. The compounds were distinguishable on the basis of their RRS spectra at 244 nm.