Utility of Raman spectroscopy in diabetes detection based on biomarker Raman bands and in antidiabetic efficacy studies of herbal extract Rotheca myricoides Hochst

Citation:
Chege BM, Birech Z, Mwangi PW, Bukachi FO. "Utility of Raman spectroscopy in diabetes detection based on biomarker Raman bands and in antidiabetic efficacy studies of herbal extract Rotheca myricoides Hochst." Journal of Raman SpectroscopyJournal of Raman Spectroscopy. 2019;50(10):1358-1366.

Abstract:

Abstract Diabetes is a disease characterized by hyperglycaemia because of insufficient or nonproduction of insulin from the pancreas. Establishing prediabetic and diabetic condition often involves monitoring levels of glucose and some amino acids in blood using nonrapid and label-dependent methods. This work reports on a method with a potential of being used for quick label-free detection of diabetes mellitus type II based on Raman spectroscopy of blood applied onto a conductive silver-smeared glass slide. We show that Raman spectral profile from blood of streptozotocin-induced diabetic Sprague Dawley rats emanates from overlap of signals from valine, leucine, isoleucine, creatine, glucose, and fructose. The Raman spectral bands associated with these biomolecules have the potential of being used in prediabetic detection and diabetes prediction. Characteristic intense peaks in diabetic rat's blood spectra were centred at wave numbers 537 cm?1 associated with valine's CO2? rocking vibration, 829 cm?1 assigned to CH2 rocking vibration in leucine and 917?960 cm?1 ascribed to C?C and C?N stretching and CH3 rocking vibrations in various biomolecules. The average intensities of these bands were sensitive to antidiabetic drug administration on the rats as their values approached those of nondiabetic rats and so could be used as diabetes biomarker bands. Statistical analyses together with evaluation of average intensities of these biomarker bands showed that the herbal extract Rotheca myricoides Hochst had greater antidiabetic effect at low dose (50 mg/kg of body weight) than at high dose (100 mg/kg of body weight). A similar result was seen with area under curve values and could act as an additional parameter in diabetes detection and prediction.

Notes:

doi: 10.1002/jrs.5619

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