ProRaman: a program to classify Raman spectra

Raman spectroscopy-based sensitive and specific detection of glycated hemoglobin

In recent years, glycated hemoglobin (HbA1c) has been increasingly accepted as a functional metric of mean blood glucose in the treatment of diabetic patients. Importantly, HbA1c provides an alternate measure of total glycemic exposure due to the representation of blood glucose throughout the day, including post-prandially. In this article, we propose and demonstrate the potential of Raman spectroscopy as a novel analytical method for quantitative detection of HbA1c, without using external dyes or reagents. Using the drop coating deposition Raman (DCDR) technique, we observe that the nonenzymatic glycosylation (glycation) of the hemoglobin molecule results in subtle but discernible and highly reproducible changes in the acquired spectra, which enable the accurate determination of glycated and nonglycated hemoglobin using standard chemometric methods. The acquired Raman spectra display excellent reproducibility of spectral characteristics at different locations in the drop and show a linear dependence of the spectral intensity on the analyte concentration. Furthermore, in hemolysate models, the developed multivariate calibration models for HbA1c show a high degree of prediction accuracy and precision--with a limit of detection that is a factor of ~15 smaller than the lowest physiological concentrations encountered in clinical practice. The excellent accuracy and reproducibility achieved in this proof-of-concept study opens substantive avenues for characterization and quantification of the glycosylation status of (therapeutic) proteins, which are widely used for biopharmaceutical development. We also envision that the proposed approach can provide a powerful tool for high-throughput HbA1c sensing in multicomponent mixtures and potentially in hemolysate and whole blood lysate samples.

Effects of different swimming exercise intensities on bone tissue composition in mice: a Raman spectroscopy study

OBJECTIVE

Raman spectroscopy was employed to evaluate the effect of different swimming intensities on femoral bone composition in an animal model.

BACKGROUND DATA

Intense swimming exercise may affect bone mineralization, and Raman technique has been shown to be effective in evaluating tissue composition (phosphate minerals and carbonate apatites - bands at 960 and 1170 cm(-1), as well as collagen matrix - amide I band at 1660 cm(-1)).

MATERIALS AND METHODS

Eighteen female Swiss Webster mice were separated into three groups (n = 6 per group) of sedentary (SED), and swimming with an intensity of 40% (PT-40) and 80% (PT-80) of the maximum load, with 6 weeks of training. Near-infrared Raman spectra (830 nm wavelength and 80 mW laser power) were obtained with a dispersive Raman spectrometer using a CCD camera and imaging spectrograph with 30-s integration time. Spectra were collected in the medial and lateral diaphysis of the femur and principal components analysis (PCA) was employed to extract features of the Raman bands of bone and to perform quantitative analysis.

RESULTS

PC1 vector resembles Raman spectra and carries information about apatite minerals and some contribution from organic matrix. A statistically significant difference was found in the PC1 scores (ANOVA, p < 0.05), indicating lower mineral concentrations in the femur in both the PT-40 and PT-80 groups compared to the SED group. These results corroborated with the radiographic assessment of bone density.

CONCLUSION

Raman technique associated with PCA statistics showed that intense swimming exercise may affect bone mineralization and remodeling in a mouse model of training.