Raman spectroscopy as a diagnostic tool for monitoring acute nephritis

Abstract

Both acute nephritis and chronic nephritis account for substantial morbidity and mortality worldwide, partly due to the lack of reliable tools for detecting disease early and monitoring its progression non-invasively. In this work, Raman spectroscopy coupled with multivariate analysis are employed for the first time to study the accelerated progression of nephritis in anti-GBM mouse model. Preliminary results show up to 98% discriminant accuracy for the severe and midly diseased and the healthy among two strains of mice with different susceptibility to acute glomerulonephritis. This technique has the potential for non-invasive or minimally-invasive early diagnosis, prognosis, and monitoring of renal disease progression.

Novel Diagnostic and Therapeutic Techniques Reveal Changed Metabolic Profiles in Recurrent Focal Segmental Glomerulosclerosis 

“…However, Raman spectroscopy was never used before to study metabolomics in FSGS. Li et al demonstrated that Raman spectroscopy combined with multivariate analysis can be a potential non-invasive diagnostic tool for nephritis in an anti-GBM mouse model 47 . We previously used Raman to detect cell stress induced by micro particles 48 .…”

Surface‐enhanced Raman scattering analysis of urine from deceased donors as a prognostic tool for kidney transplant outcome

“…Dominant Raman peak is at 1620 cm −1 , which corresponds to the ring stretching mode of porphyrin. Tentative Raman band assignments are shown in Table . Because the urine samples were stored at −80 °C and thawed before SERS measurements, the impact of freeze and thaw cycle on SERS spectra was investigated.…”

3-Dimensional Plasmonic Substrates Based on Chicken Eggshell Bio-Templates for SERS-Based Bio-Sensing

“…Some distinctive spike features are observed in the difference spectrum which implies the difference in the SERS spectra. More sophisticated statistical techniques, e.g., hierarchical cluster analysis (HCA) and/or discriminant analysis (DA) can be employed to obtain quantitative bacterial identification/classification [ 46 , 47 , 48 ]. Reproducibility has been an issue for the widespread adoption of SERS-based bacteria identification since the enhancement phenomenon depends on the microscopic morphology and stability of the SERS substrate.…”