Literature DB >> 33988040

Vibrational Spectroscopy for Detection of Diabetes: A Review.

Nicole M Ralbovsky1, Igor K Lednev1.   

Abstract

Type II diabetes mellitus (T2DM) is a metabolic disorder that is characterized by chronically elevated glucose caused by insulin resistance. Although T2DM is manageable through insulin therapy, the disorder itself is a risk factor for much more dangerous diseases including cardiovascular disease, kidney disease, retinopathy, Alzheimer's disease, and more. T2DM affects 450 million people worldwide and is attributed to causing over four million deaths each year. Current methods for detecting diabetes typically involve testing a person's glycated hemoglobin levels as well as blood sugar levels randomly or after fasting. However, these methods can be problematic due to an individual's levels differing on a day-to-day basis or being affected by diet or environment, and due to the lack of sensitivity and reliability within the tests themselves. Vibrational spectroscopic methods have been pursued as a novel method for detecting diabetes accurately and early in a minimally invasive manner. This review summarizes recent research, since 2015, which has used infrared or Raman spectroscopy for the purpose of developing a fast and accurate method for diagnosing diabetes. Based on critical evaluation of the reviewed work, vibrational spectroscopy has the potential to improve and revolutionize the way diabetes is diagnosed, thereby allowing for faster and more effective treatment of the disorder.

Entities:  

Keywords:  FT-IR; Fourier transform infrared; Raman spectroscopy; Vibrational spectroscopy; biomarker; chemometrics; diabetes; diagnostics; infrared spectroscopy

Year:  2021        PMID: 33988040     DOI: 10.1177/00037028211019130

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  1 in total

1.  A Novel Method for Detecting Duchenne Muscular Dystrophy in Blood Serum of mdx Mice.

Authors:  Nicole M Ralbovsky; Paromita Dey; Andrew Galfano; Bijan K Dey; Igor K Lednev
Journal:  Genes (Basel)       Date:  2022-07-27       Impact factor: 4.141

  1 in total

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