Fluorescence photobleaching of urine for improved signal to noise ratio of the Raman signal - An exploratory study.

Urine analysis is an important clinical test routinely performed in pathology labs for disease diagnosis and prognosis. In recent years, near-infrared Raman spectroscopy has drawn considerable attention for urine analysis as it can provide rapid, reliable, and reagent-free analysis of urine samples. However, one important practical problem encountered in such Raman measurements is the orders of magnitude stronger spectral background preventing one to utilize the full dynamic range of the detector which is required for the measurement of Raman signal with good signal-to-noise ratio (SNR). We report here the results of an exploratory study carried out on human urine samples to show that the photobleaching, which is a major disadvantage during the fluorescence measurement, could be utilized for suppressing the measured background to improve the SNR of the Raman peaks. It was found that once the photobleaching reached its plateau, there were improvements by ~67% and ~47% in the SNR and the signal to background ratio (SBR), respectively, of the Raman signals as compared to the spectra measured at the start of acquisition. Further, the reduced background also allowed us to utilize the full dynamic range of the detector at increased integration time without saturating the detector indicating the possibility of obtaining an improved detection limit.

Nanotrap-Enhanced Raman Spectroscopy: An Efficient Technique for Trace Detection of Bioanalytes.

Reliable diagnosis of disease using body fluids requires sensitive and accurate detection of disease-specific analytes present in the fluid. In recent years, there has been increasing interest in using surface-enhanced Raman spectroscopy (SERS) for this purpose. The demonstrable signal enhancement and sensitivity of SERS makes it ideally suited for detection of a trace quantity of any analyte. However, lack of reproducibility along with large spatial variability in the measured Raman intensities due to differential (and often random) distribution of surface "hot spots" limits its routine clinical use. We propose here a technique, nanotrap-enhanced Raman spectroscopy (NTERS), for overcoming these long-standing limitations and challenges of SERS. In this technique, hot spots are formed by drying up a microvolume drop of the liquid, containing the mixture of nanoparticles and analytes in the focal volume of the Raman excitation laser, and the Raman signal is detected from these spots containing the analytes localized within the nanoparticle aggregates. The performance of the technique was evaluated in detecting trace quantities of two Raman-active analytes, Rhodamine 6G (R6G) and urea. It was found that R6G and urea could be detected down to a concentration of 50 nM with signal-to-noise ratio (SNR) value of ∼75 and 4 mM with SNR value of ∼500, respectively. A comparison with SERS revealed that NTERS not only had significantly superior (around 2 orders of magnitude) signal enhancement but also had high reproducibility because of its intrinsic ability to form nanoparticle aggregates with high repetitiveness. Another advantage of NTERS is its simplicity and cost effectiveness as it does not require any specialized substrate.

Cone-shell Raman spectroscopy (CSRS) for depth-sensitive measurements in layered tissue.

We report the development of a depth-sensitive Raman spectroscopy system using the configuration of cone-shell excitation and cone detection. The system uses a 785 nm diode laser and three identical axicons for Raman excitation of the target sample in the form of a hollow conic section. The Raman scattered light from the sample, passed through the same (but solid) conic section, is collected for detection. Apart from its ability of probing larger depths (~ few mm), an important attraction of the system is that the probing depths can be varied by simply varying the separation between axicons in the excitation arm. Furthermore, no adjustment is required in the sample arm, which is a significant advantage for noncontact, depth-sensitive measurement. Evaluation of the performance of the developed setup on nonbiological phantom and biological tissue sample demonstrated its ability to recover Raman spectra of layers located at depths of ~2-3 mm beneath the surface.